WO2015029452A1 - Analyzer, analysis method, program, and skin sample collection kit - Google Patents

Abstract

　Provided is an analyzer for analyzing a skin image taken of the surface of skin, the analyzer being provided with: a sulcus cutis detection unit for detecting lines corresponding to sulci cutis included in the skin image; and an index calculation unit for calculating an index representing the state of the skin on the basis of the arrangement of the lines. Also provided is a skin sample collection kit for collecting a sample of the surface of the skin to be analyzed by the analyzer, the skin sample collection kit being provided with: an analysis fluid coated on the surface of the skin, the analysis fluid hardening when dried; and a sheet bonded to the dried analysis fluid.

Description

Analysis device, analysis method, program, and skin sample collection kit

The present invention relates to an analysis apparatus, an analysis method, and a program for analyzing a skin image obtained by imaging the surface of the skin. The present invention also relates to a skin sample collection kit for collecting a sample of the surface of the skin to be analyzed by the analysis apparatus.

Conventionally, the skin area of the skin surface and the depth of the skin groove are measured, and the skin age (the difference between the ideal state of the skin and the actual measurement value is calculated from the measured values in the form of the corresponding age or age difference. It is known to calculate
[Prior art documents]
[Patent Literature]
[Patent Document 1] Japanese Patent No. 4059829

However, in order to measure the skin area of the skin and the depth of the skin groove, it is necessary to pass the subject's skin surface with a magnifying camera, so the subject must go to where the device is, The skin condition could not be easily evaluated.

In order to solve the above-described problem, in the first aspect of the present invention, an analysis device that analyzes a skin image obtained by imaging the surface of the skin, and detects a line corresponding to a skin groove included in the skin image. An analysis device, an analysis method, and a program are provided that include a skin groove detection unit that performs an index value calculation unit that calculates an index value that represents a skin state based on an arrangement state of lines.

In the second aspect of the present invention, there is a skin sample collection kit for collecting a sample of the surface of the skin to be analyzed by the analysis device of the first aspect, which is applied to the surface of the skin, dried and solidified. Provided is a skin sample collection kit comprising an analysis liquid and a sheet that adheres the dried analysis liquid.

Note that the above summary of the invention does not enumerate all the necessary features of the present invention. In addition, a sub-combination of these feature groups can also be an invention.

An example of a functional structure of the skin condition analysis system 10 which concerns on this embodiment is shown. An example of the sheet | seat 100 which adhere | attaches the analysis liquid apply | coated and dried to the skin which concerns on this embodiment is shown. An example of the container 120 for accommodating the sheet | seat 100 which concerns on this embodiment is shown. The analysis processing flow in the skin condition analysis system 10 which concerns on this embodiment is shown. The primary lines 302 and 304, the secondary line 306, and the polygon 308 which the skin groove detection part 34 which concerns on this embodiment detect are shown. An example of the skin texture index value map used by the index value calculation unit 36 and the skin age calculation unit 38 according to the present embodiment is shown. An example of the moisturizing index value map used by the moisturizing detection unit 42 according to the present embodiment is shown. An example of the data which the memory | storage part 40 which concerns on this embodiment stores is shown. An example of the contents of the questionnaire concerning this embodiment is shown. An example of the report which the output part 52 which concerns on this embodiment produces is shown. 2 shows an exemplary hardware configuration of a computer 1900 according to the present embodiment.

Hereinafter, the present invention will be described through embodiments of the invention. However, the following embodiments do not limit the invention according to the claims. In addition, not all the combinations of features described in the embodiments are essential for the solving means of the invention.

FIG. 1 shows an example of a functional configuration of a skin condition analysis system 10 according to the present embodiment. For example, the skin condition analysis system 10 captures a sample of the collected skin surface to acquire a skin image, analyzes the acquired skin image, and outputs the analysis result as a report. As a result, the skin condition analysis system 10 can evaluate the skin condition without illuminating the subject's skin surface with a magnifying camera, so that the subject can easily evaluate the skin condition without going to the device. Can receive.

The skin condition analysis system 10 includes a microscope 20, an analysis device 30, and an output unit 52. The microscope 20 includes a lens unit 22 and an imaging unit 24. The lens unit 22 expands the subject light of the analysis solution or skin sample adhered and dried on the sheet 100 to a predetermined magnification. The lens unit 22 may be replaceable so that it can be changed to any magnification as necessary.

The imaging unit 24 is, for example, a CCD (Charge Coupled Device Image Sensor) or a CMOS (Complementary Metal Oxide Semiconductor Semiconductor Image Sensor), and images the subject light magnified by the lens unit 22. Note that the number of times that one sample is imaged may be one or a plurality of times. The microscope 20 outputs the image captured by the imaging unit 24 to the analysis device 30 as a skin image.

The analysis device 30 analyzes a skin image obtained by imaging the surface of the skin. The analysis device 30 includes a skin image selection unit 32, a skin groove detection unit 34, an index value calculation unit 36, a skin age calculation unit 38, a storage unit 40, a moisturization detection unit 42, a statistical processing unit 44, a history processing unit 46, and a damage factor. An analysis unit 48 and a cosmetic selection unit 50 are provided.

Skin image selection unit 32 selects at least one skin image from the plurality of skin images when a plurality of skin images are input from the microscope 20 for one sample. For example, the skin image selection unit 32 selects a skin image having the highest contrast as a skin image for analysis. Alternatively, the skin image selection unit 32 may select two or more skin images as analysis skin images, or may select an average image of two or more skin images as analysis skin images. Good. When there is only one skin image input from the microscope 20, the input skin image is selected as a skin image for analysis regardless of the contrast level.

Further, the skin image selection unit 32 is for skin texture analysis for analyzing the texture of the skin, or for moisture retention analysis for analyzing skin moisture. May be determined. For example, the skin image selection unit 32 determines the type of the skin image based on an operator's designation or an identification code input from the microscope 20. When the skin image is for skin texture analysis, the skin image selection unit 32 outputs the selected skin image to the skin groove detection unit 34 and the storage unit 40, and the skin image is for moisture retention analysis. If there is, the selected skin image is output to the storage unit 40 and the moisturizing detection unit 42.

The skin groove detecting unit 34 detects a line corresponding to the skin groove included in the skin image. The skin groove detection unit 34 detects at least one of the regularity of the line arrangement and the continuity of the line as the line arrangement state. Specifically, the skin groove detection unit 34 detects a plurality of primary lines having a width satisfying a predetermined first reference width from the skin image and arranged in a grid pattern. The skin groove detecting unit 34 further detects a plurality of secondary lines extending between a plurality of primary lines and having a width satisfying a second reference width narrower than the first reference width. The skin groove detection unit 34 inputs the detected data to the index value calculation unit 36.

The index value calculation unit 36 calculates the first index value calculated based on at least one of the regularity of the array of primary lines and the continuity of each primary line, the regularity of the array of secondary lines, and each secondary A skin texture index value is calculated based on the second index value calculated based on at least one of the line continuity. The index value calculation unit may calculate the skin texture index value further based on the size of a region surrounded by a plurality of primary lines and a plurality of secondary lines. The index value calculation unit 36 outputs the calculated skin texture index value to the skin age calculation unit 38 and the storage unit 40.

The skin age calculation unit 38 calculates the skin age based on the skin texture index value. As an example, the skin age calculation unit 38 sets the age associated with the skin texture index value as the skin age. The skin age calculation unit 38 outputs the calculated skin age to the storage unit 40.

When the skin image is input from the skin image selection unit 32, the moisturizing detection unit 42 detects the size or the like of the cells included in the skin image. The moisturizing detection unit 42 further calculates a moisturizing index value based on the cell size and the degree of cell aggregation. The moisture retention detection unit 42 outputs the calculated moisture retention index value to the storage unit 40.

The storage unit 40 stores the subject's actual age, skin texture index value, and / or skin age corresponding to each of the plurality of subjects. Moreover, the memory | storage part 40 stores a moisturizing index value corresponding to each of a some subject. Moreover, the memory | storage part 40 may store the log | history data which has two or more sets containing an object person's real age, an index value, and at least one of skin age about one object person. Moreover, the memory | storage part 40 may store the group containing at least one of a subject's real age, the questionnaire result regarding a subject's skin, an index value, and skin age. Moreover, the memory | storage part 40 may store the group containing at least one of a subject's real age, the questionnaire result regarding a subject's skin, the cosmetics which the subject is using, an index value, and skin age.

The statistical processing unit 44 calculates, for each skin texture index value stored in the storage unit 40, statistical data of the actual age of the subject who has been analyzed that the skin condition is the skin texture index value. The statistical processing unit 44 stores the calculated statistical data in the storage unit 40. Based on the result of comparing at least one of the latest index value and skin age with history data of at least one of the previous index value and skin age, the history processing unit 46 determines which age of the subject the skin condition is. Calculate whether the condition has been improved. The history processing unit 46 stores the calculated improvement data in the storage unit 40.

The damage factor analysis unit 48 analyzes the damage factor given to the skin for each subject's skin management and the subject's lifestyle based on the questionnaire results stored in the storage unit 40. The damage factor analysis unit 48 stores the analyzed damage factor in the storage unit 40. The cosmetic selection unit 50 selects cosmetics that improve the skin condition for each characteristic of the subject's skin based on the questionnaire results stored in the storage unit 40. The cosmetic selection unit 50 stores the selected cosmetic in the storage unit 40.

The output unit 52 outputs the result of the analysis device 30 analyzing the skin image. The output unit 52 may be a printer that prints analysis results in a predetermined format, a display that displays analysis results in a predetermined format, or an arbitrary terminal via a network. It may be a transmission device that transmits an analysis result to a predetermined format (for example, a subject's smartphone).

In FIG. 1, the analysis device 30 has a configuration in which each unit is provided in the device. However, instead of this, the analysis device 30 may have a configuration in which each function is distributed to a plurality of devices, and some of the functions are included. It may be realized by an external server or the like, and may be realized by performing communication via a network. As an example of this, at least a part of the functions of the storage unit 40 is realized by a server or the like on the network, and other functions of the analysis device 30 are the subject's skin image, actual age, skin age via the network. The skin texture index value, the moisturizing index value, and / or at least a part of the history data is acquired from the server or the like and processed. In such a configuration, the server or the like holding the data associated with the target person may permit the data access on the condition that the access request from the other function of the analysis apparatus 30 is correctly authenticated. Good.

FIG. 2 shows an example of a sheet 100 that adheres the analysis liquid applied to the skin and dried according to the present embodiment. As an example, two or more sheets 100 are included in the skin sample collection kit. There are two types of sheets 100, a skin texture analysis sheet and a moisture retention analysis sheet. For the skin texture analysis sheet, the analysis liquid contained in the skin sample collection kit is applied to the skin, and the dry analysis liquid is adhered. The sheet for moisturizing analysis adheres cells on the surface of the skin without applying the analysis solution to the skin. Note that the number of sheets 100 included in the skin sample collection kit may be only one. In this case, for example, a plurality of adhesive spots may be provided on the sheet 100.

The sheet 100 has an identification unit 102 for identifying a skin texture analysis sheet and a moisture retention analysis sheet. For example, in the identification unit 102, red is applied to the skin texture analysis sheet, and blue is applied to the moisture retention analysis sheet.

The identification unit 102 is imaged by the microscope 20. The microscope 20 detects a color from an image obtained by capturing the identification unit 102 and outputs an identification code corresponding to the detected color to the skin image selection unit 32. Thus, the operator can cause the analysis device 30 to analyze the different sample sheets 100 collected by the subject without being mistaken in the analysis process. When the operator identifies the sheet 100 by visual observation, for example, by microscopic observation, the identification unit 102 may not be provided on the sheet 100.

The sheet 100 includes a support unit 104 on which the subject has the sheet 100, a sample collection unit 106 that is applied to the subject's skin and dried and / or adheres to the surface of the subject's skin, and the sample collection unit 106. It further has an adhesion protection part 108 for maintaining the adhesiveness. The sample collection unit 106 is exposed by peeling the adhesive protection unit 108 as shown in FIG. The subject collects the sample for skin texture analysis by bringing the exposed sample collection unit 106 into contact with the analysis solution dried on the skin surface, and the exposed sample collection unit 106 is used as the surface of the subject's skin. A sample for moisturizing analysis is taken by contact.

FIG. 3 shows an example of a container 120 for storing the sheet 100 adhered with the dried analysis liquid according to the present embodiment. The container 120 is included in the skin sample collection kit, and includes a lid part 122 and a storage part 124. On the back side of the lid 122, a sticker 126 in which the name of the subject person and the ID given to the subject person are written in advance is affixed. Such an ID may be, for example, a string of letters and / or numbers, a one-dimensional or two-dimensional barcode, or a QR code (registered trademark). With this seal 126, it is possible to avoid a situation in which the analysis cannot be performed even if the subject forgets to write the name and ID. Note that the seal 126 may be attached to the front side of the lid 122.

The accommodating part 124 includes, for example, two accommodating spaces 130 and 132 for accommodating two sheets partitioned by the space sill part 128 side by side. The accommodation space is not limited to two and may be two or more. Thereby, the sheet | seat which collected the sample of several places, such as a back of the hand, an upper arm, and a heel, can be accommodated, and the subject can know more skin states. Moreover, the accommodation space of the container 120 may be one. Thereby, the size of the container 120 can be reduced, for example, when analyzing only one for skin texture analysis or moisture retention analysis.

The accommodating portion 124 has a thickness that is sufficiently larger than the thickness of the sheet 100. For this reason, the sheet | seat 100 after extract | collecting a sample does not contact | adhere to the cover part 122. FIG. The accommodating portion 124 may be made of a material such as hard paper or plastic. As a result, the sample in the storage portion 124 can be protected even when an external impact is applied to the storage portion 124.

Also, the skin sample collection kit contains an analysis solution that is applied to the surface of the skin and dried and solidified. The analysis liquid may contain at least one of pullulan, alginic acid, and starch. The analysis solution does not contain cyanoacrylate, which is a component of the instantaneous adhesive. For this reason, troubles due to misuse do not occur, so that a general subject who is not an expert can also take a sample. Furthermore, the location where the sample is collected is not limited to a specific location such as the back of the hand or the upper arm. For example, the sample can be collected from a location such as the face, specifically the cheek or the eyes.

FIG. 4 shows an analysis processing flow in the skin condition analysis system 10 according to the present embodiment. In S <b> 1, the skin condition analysis system 10 captures a sample collected by the subject using the skin sample collection kit, for example, four times with the microscope 20 and acquires four skin images. In addition, the microscope 20 captures an image of the identification unit 102 of the sheet 100, detects the color of the identification unit 102, and generates an identification code corresponding to the color. The microscope 20 outputs the four skin images and the skin image identification code to the skin image selection unit 32. Note that the number of imaging is not limited to four, and may be more or less than four. Similarly, the number of skin images to be acquired is not limited to four. When the operator visually identifies the sample, the skin image identification code is output to the skin image selection unit 32 in accordance with the operator's output operation.

In S2, the skin image selection unit 32 determines whether the skin image acquired based on the identification code is for skin texture analysis or for moisturizing analysis. As a result of determining the identification code, the skin condition analysis system 10 advances the process to S3 when the skin image is for skin texture analysis.

In S3, the skin image selection unit 32 calculates the luminance difference between the darkest part and the brightest part in the skin image, and selects the skin image having the largest luminance difference. That is, the skin image selection unit 32 selects the skin image with the highest contrast from the four skin images as the skin image for analysis. The skin image selection unit 32 transmits the selected skin image for analysis to the skin groove detection unit 34. The skin image selection unit 32 may transmit the selected skin image for analysis to the storage unit 40.

The skin groove detection unit 34 detects a portion darker than a predetermined threshold in the skin image, and detects a primary line corresponding to the skin grooves arranged in a lattice shape and a secondary line extending between the primary lines. . Note that whether the skin groove appears dark or bright in the skin image depends on the type of microscope 20 used. The skin groove detection unit 34 may detect a primary line and a secondary line by detecting a portion brighter than the threshold value in the skin image. The skin groove detection unit 34 outputs the detected primary and secondary lines to the index value calculation unit 36 as detection data. In addition, the detection method of a primary line and a secondary line is later mentioned in relation to FIG.

In S4, the index value calculation unit 36 calculates a skin texture index value indicating the texture of the skin based on the detection data, and outputs the calculated skin texture index value to the skin age calculation unit 38 and the storage unit 40. In S <b> 5, the skin age calculation unit 38 calculates the skin age based on the skin texture index value, and outputs the calculated skin age to the storage unit 40. A skin texture index value calculation method and a skin age calculation method will be described later with reference to FIG.

On the other hand, in S2, the skin condition analysis system 10 advances the process to S8 when the skin image is not for skin texture analysis (No). In S8, the skin image selection unit 32 selects, as the skin image for analysis, the one having the highest contrast from the four skin images as the skin image for skin texture analysis, and selects the selected skin image for analysis. Is transmitted to the moisturizing detection unit 42. The skin image selection unit 32 may transmit the selected skin image for analysis to the storage unit 40.

In S9, the moisturizing detection unit 42 detects the distribution mode of light and shade in the skin image based on a predetermined threshold in the skin image. The moisturizing detection unit 42 detects the characteristics of the cells on the surface of the skin from the distribution of shades in the skin image, and advances the process to S10. In S <b> 10, the moisturizing detection unit 42 calculates the moisturizing index value based on the characteristics of the cells on the surface of the skin, and outputs the moisturizing index value to the storage unit 40. A method for detecting cells on the surface of the skin and a method for calculating the moisturizing index value will be described later with reference to FIG.

In S6, the storage unit 40 stores the skin texture index value, skin age, and moisturizing index value, and advances the process to S7. In addition, the memory | storage part 40 stores an analysis result cumulatively whenever it analyzes the skin texture index value, skin age, and moisturizing index value. The storage mode of the storage unit 40 will be described later with reference to FIG.

In S <b> 7, the statistical processing unit 44 calculates statistical data (for example, an average value such as a skin texture index value) based on the value for each skin texture index value, skin age, and moisturizing index value stored cumulatively in the storage unit 40. ) Is calculated. The statistical processing unit 44 outputs the calculated statistical data to the storage unit 40, stores the statistical data in the storage unit 40, and advances the process to S8. The statistical data calculation method will be described later with reference to FIG.

In S8, the output unit 52 refers to the storage unit 40 to acquire analysis result data (for example, skin texture index value and / or skin age index value and moisturizing index value), and the acquired analysis result according to a predetermined format. Create reports based on the data. The report format to be created will be described later with reference to FIG.

The skin condition analysis system 10 ends the analysis process when the output unit 52 finishes creating the report. The created report will be mailed to the subject. Therefore, the subject can receive an evaluation of the skin condition simply by collecting a skin sample with the skin sample collection kit and mailing the collected sample.

FIG. 5 shows an example of a skin image for skin texture analysis. The skin image includes a plurality of primary lines 302 and 304, a plurality of secondary lines 306, and a plurality of polygons 308. The primary lines 302 and 304 are lines that have a width satisfying a predetermined first reference width and are arranged in a grid pattern. It is desirable that the primary lines 302 and 304 are long in the aligned direction and are narrowly spaced at equal intervals. The secondary line 306 is a line extending between the plurality of primary lines 302 and 304 and having a width satisfying a second reference width that is narrower than the first reference width. It is desired that the secondary line 306 is long and has a regularity that penetrates diagonally through the region surrounded by the primary lines 302 and 304.

The polygon 308 is an area surrounded by a plurality of primary lines 302 and 304 and a plurality of secondary lines 306, and depends on the presence of the plurality of primary lines 302 and 304 and the plurality of secondary lines 306. Therefore, the polygon 308 is desired to have a fine size because of the desired form of the primary lines 302 and 304 and the secondary line 306. Therefore, the texture of the skin depends on the length, interval, and direction of the primary lines 302 and 304, the length and regularity of the secondary lines 306, and the size of the polygon 308 formed from these lines.

The skin groove detection unit 34 compares, for example, the luminance of the skin image with a predetermined threshold, and detects a portion where the luminance is lower than the threshold as a dark portion. The skin groove detection unit 34 detects a series of detected dark portions. The skin groove detecting unit 34 detects a plurality of lines arranged in a lattice shape as primary lines 302 and 304 having a width in which the continuous dark portions satisfy a predetermined first reference width. As with the primary lines 302 and 304, the skin groove detection unit 34 extends between the plurality of primary lines 302 and 304, and a plurality of widths satisfying a second reference width that is narrower than the first reference width. The line is further detected as a secondary line 306.

Here, the skin groove detection unit 34 detects an object in the skin image, and based on at least one of the detected object thickness, depth, and volume, the primary lines 302 and 304, the secondary line 306, and The polygon 308 may be detected.

For example, the skin groove detection unit 34 detects, as an object, a region in which pixels having luminance lower than a threshold value in a skin image are continuous, and the length and width of a rectangle circumscribing the object, the area of the object (that is, included in the object) The number of pixels), the angle of the object with respect to a reference direction (for example, the horizontal direction), and the like, and the thickness, depth, and volume of the object may be calculated using these.

Further, the skin groove detection unit 34 may calculate the total OD or total density (Total OD) obtained by multiplying the average OD or average density (Mean Optical Density) of each pixel by the area of the object. That is, when the darker part in the skin image corresponds to the deeper part of the skin groove, the density of the object in the skin image represents the depth of the skin groove. Therefore, the total density is an index representing the volume of the object.

Further, the skin groove detection unit 34 may calculate a value obtained by dividing the area of the object by the length of the center axis of the object (or the length of the long side of the rectangle circumscribing the object) as the thickness of the object. Good. Further, the skin groove detection unit 34 may calculate an OD thickness obtained by multiplying the average density of each pixel by the thickness of the object. The OD thickness is an index representing the volume per length of the object.

Further, the skin groove detection unit 34 may calculate the integrated OD thickness by multiplying the total density by the thickness of the object. The integrated OD thickness is an index that emphasizes both the volume of the object and the thickness of the object.

The skin groove detection unit 34 may detect the primary lines 302 and 304 and / or the secondary line 306 using the detected object thickness, OD thickness, or integrated OD thickness as the object width. Good.
Further, the skin groove detection unit 34 uses the average OD as the depth of the object, and determines whether the average OD is equal to or higher than a reference value corresponding to the primary line and / or the secondary line. It may be used as a factor for determining the next line.
Further, the skin groove detection unit uses the total OD or the integrated OD thickness as the volume of the object, and determines whether or not these are equal to or greater than a reference value corresponding to the primary line and / or the secondary line. You may use as a factor which determines a line.

FIG. 6 shows an example of a skin texture index value map. The skin texture index value map includes a judgment standard, a skin texture state, a skin texture index value, and a skin age. The criterion is a criterion for determining the state of the primary line, the state of the secondary line, and the state of the polygon size. There are a plurality of determination criteria for each primary line, secondary line, and polygon, and a score is assigned to each determination criterion.

As an example, the criteria for judging the state of the primary line are scored as follows. In the presence, “4” points are assigned to the criteria for determining whether a regular, well-organized grid in a plurality of directions forms a continuous line. In the presence, a “3” point is assigned to a criterion for determining whether a regular, well-organized grid is broken in a plurality of directions. In the presence, “2” points are assigned to the judgment criteria for judging whether the direction is irregular and the direction is unidirectional and whether it is a broken line. In the presence, “1” point is assigned to the criterion for determining whether there is only one direction, no grid, and a broken line. A “0” point is assigned to a criterion for which the primary line cannot be confirmed.

Also, as an example, the criteria for judging the state of the secondary line are scored as follows. In the presence, “4” points are assigned to the criteria for judging whether regular, clear and continuous. In the presence, “3” points are assigned to the judgment criteria that are regular but partly discontinuous. In the presence, “2” points are assigned to the judgment criteria for judging whether or not they are somewhat irregular and discontinuous. A “1” point is assigned to the criterion for determining whether or not the image is almost visible. A “0” point is assigned to a criterion for which a secondary line cannot be confirmed.

Also, as an example, the criteria for judging the state of the polygon size are scored as follows. A “4” point is assigned to a criterion for determining whether or not the size of the polygon is smaller than a predetermined size. A point “3” is assigned to the criterion for determining whether or not the size of the polygon is within a predetermined range (for example, medium size). A “2” point is assigned to a criterion for determining whether or not the size of the polygon is larger than a predetermined range size (for example, medium or larger). A “1” point is assigned to a criterion for determining whether or not the size of the polygon is larger than a predetermined size (for example, a very large size). If the primary and secondary lines cannot be confirmed, a “0” point is assigned.

Note that the criteria for determining the state of the primary line, the state of the secondary line, and the state of the polygon size are not limited to the above. For example, the determination criteria may be increased, or the determination items may be changed. Alternatively, the score assigned to the determination criterion may be changed.

The index value calculation unit 36, for example, regularity of the arrangement of a plurality of primary lines (the narrowness of the interval and / or the equality of the intervals), and the continuity of each primary line (the length that the line continues without being cut) ), It is detected which of the judgment criteria in the skin texture index value map the primary line state corresponds to, and the score assigned to the relevant judgment criterion is calculated as the first index value. Further, the index value calculation unit 36 further determines the primary line state as one of the determination criteria based on the uniformity of a plurality of primary lines (line width and / or line arrangement direction) as a characteristic of the primary line. And the score assigned to the corresponding criterion may be calculated as the first index value.

The index value calculation unit 36, for example, regularity of the arrangement of a plurality of secondary lines (the narrowness of the interval and / or the equality of the intervals) and the continuity of each secondary line (the length that continues without breaking the line) Based on at least one of the above, it is detected which of the judgment criteria in the skin texture index value map the state of the secondary line corresponds to, and the score assigned to the relevant judgment criteria is calculated as the second index value . The index value calculation unit 36 may calculate a total score or an average score of the calculated first index value and second index value, and may use the total score or the average score as a skin texture index value.

The index value calculation unit 36 may calculate the skin texture index value based on at least one of the regularity of a plurality of primary lines and the continuity of each primary line. The skin texture index value may be calculated based on at least one of regularity and continuity of each secondary line.

The index value calculation unit 36 may further calculate a skin texture index value based on the size of a region surrounded by a plurality of primary lines and a plurality of secondary lines, that is, the size of a polygon. The index value calculation unit 36 calculates the size of the region surrounded by the plurality of primary lines and the plurality of secondary lines by counting the number of pixels in the region surrounded by the plurality of primary lines and the plurality of secondary lines. To do. As an example, the index value calculation unit 36 calculates an average value of the sizes of regions surrounded by a plurality of primary lines and a plurality of secondary lines within a predetermined range or the entire range of the skin image.

The index value calculation unit 36 compares the calculated average value of the area with the size of the determination criterion, detects which of the determination criteria in the skin texture index value map the polygon size corresponds to, and determines the determination The score assigned to the reference is calculated as the third index value. The index value calculation unit 36 may calculate a total value or an average value of the first index value, the second index value, and the third index value, and may use the total value or the average value as a skin texture index value.

The index value calculation unit 36 uses whether or not the variation in the angle of the object in the skin image with respect to the reference direction is within the reference range as a factor for determining the regularity of the arrangement of the primary line and the secondary line. Also good.
Further, the index value calculation unit 36 may use the size of coverage indicating the ratio of the area occupied by the object in the skin image as a factor for determining the skin texture index value. In this case, the index value calculation unit 36 may increase the skin texture index value as the coverage increases.

In the skin texture index value map of FIG. 6, the skin texture state and the skin texture index value correspond to the sum of the first index value, the second index value, and the third index value. For this reason, the texture of the skin becomes finer if the total value of the index values is equal to the maximum value (for example, 12), and the texture of the skin becomes rougher as the total value of the scores is farther from the maximum value. (See skin image). As an example, the skin texture index value is 0 to 12, but the skin texture index value may be 0 to 10 or 0 to 15. The skin texture index value may be set appropriately. Good.

The skin age is associated with the skin texture index value in the skin texture index value map of FIG. The skin age may represent an average age range corresponding to each skin texture index value. For this reason, for example, when the skin texture index value of a subject whose actual age is 32 years old is “6”, the skin texture of the subject is often the texture of skin whose actual age is between 40 and 45 years old. It is equivalent to.

FIG. 7 shows an example of a moisturizing index value map. The moisturizing index value map has a determination standard, a skin moisturizing state, and a moisturizing index value. Judgment criteria are criteria for judging the state of isolated cells (CI), small packet cells (PPC), large packet cells (GPC), thickened areas (Ep), and dandruff (Sq). A score is assigned for each criterion.

For example, there are many isolated cells (CI), many small packet cells (PPC), little or no large packet cells (GPC), low thickness, and no dandruff “12” points are assigned to the criterion for determining whether or not. In addition, in the presence of a large or small number of isolated cells, “9” points are assigned to the judgment criteria for determining whether there is a possibility that the presence of GPC is large in PPC, the thickness is small, and the scale is present. ing.

Also, the criteria for determining whether a small number of isolated cells or some PPCs are absent or present, and that there may be many GPCs, moderate thickening (white +), and scales are “ 6 "points are assigned. Also, “3” is used as a criterion for determining whether or not a small number of isolated cells are present or present, some PPCs, many GPCs, severe thickening (white ++), and many scales. Points are assigned. Also, if the criteria are not met, a score of 3 or less is assigned.

The skin moisturizing state and the moisturizing index value are associated with the score assigned to the criterion. As an example, a state where the skin moisturizing barrier function is sufficient and / or a state where the cell has sufficient moisture is associated with the “12” point. Further, a state where the skin moisturizing barrier function is normal and / or a state where moisture is present in the cells is associated with a “9” point. In addition, the state where the skin moisturizing barrier function is low and / or the state where the cell is low in water is associated with the “6” point. Further, the state in which the skin moisturizing barrier function is lost and / or the state in which the cells are dry is associated with the “3” point. Further, the state in which the skin moisturizing barrier function is almost completely lost and / or the state in which the cells are extremely dry are associated with the “<3” point.

The moisturizing detection unit 42 detects the distribution of shades in the skin image based on a predetermined threshold in the skin image, and detects the characteristics of cells on the surface of the skin from the distribution of shades in the skin image. The moisturizing detection unit 42 determines which criterion of the moisturizing index value map corresponds to the detected feature, and calculates the score assigned to the corresponding criterion as the moisturizing index value. In such a determination, the moisturizing detection unit 42 compares the size of cells, the number / ratio of cells, the characteristics of the cells, etc. with a predetermined threshold value, etc. You may specify.

For example, the moisturizing detection unit 42 is a light / dark distribution mode in which the distribution of gray portions in the skin image has a small distribution of white portions as a feature of cells on the surface of the skin and the dark portions uniformly exist. There are many isolated cells (CI), many small packet cells (PPC), little or no large packet cells (GPC), low thickness, and no dandruff. If detected, it is determined that the feature corresponds to the determination criterion at the top of the moisturizing index value map, and the score “12” assigned to the determination criterion is calculated as the moisturizing index value “12”. As an example, the moisturizing index value is set to <3 to 12 steps, but the moisturizing index value may be 0 to 10 or 0 to 15, and the moisturizing index value may be set as appropriate. The moisturizing index value may be displayed, for example, as a percentage where the highest score of the moisturizing index value is “100%”.

In the above example, the part away from the skin looks white, and the uniformly existing cells appear dark. However, the black and white and the light and shade of the skin image may also depend on the type of the microscope 20 used. Different.

FIG. 8 shows an example of data stored in the storage unit 40. The storage unit 40 stores, for example, at least one of the skin texture index value and the skin age and the moisturizing index value in association with the unique information of the subject for each analysis. In addition, the memory | storage part 40 may store an analysis date etc. in addition to these. The storage unit 40 may store, as an example of the target person's unique information, the ID given to the target person at the time of ordering, and the name, sex, living area, occupation, and actual age received at the time of the order. The unique information is not limited to these. For example, the result of a questionnaire answered by the subject may be stored in association with the unique information of the subject. The contents of the questionnaire will be described later with reference to FIG.

The statistical processing unit 44 stores, for each skin texture index value stored in the storage unit 40, statistical data (for example, average, median value) of the subject's real age analyzed that the skin condition is the skin texture index value , Variance, etc.), and the calculated statistical data is stored in the storage unit 40. The statistical processing unit 44 may further update the skin age and / or its range for each skin texture index value based on the calculated statistical data. The statistical processing unit 44 can improve the accuracy of the skin age associated with the skin texture index value using the statistical data.

FIG. 9 shows an example of questionnaire contents. The questionnaire may include a questionnaire sheet attached to the skin sample collection kit and may be answered by the subject or may be answered when the subject orders the skin sample collection kit. Although six questionnaire items are described in the questionnaire sheet shown in FIG. 9, the number and contents of the questionnaire items are not limited to these. In addition, the questionnaire may be performed not only at the first time but also after the first time, and the number of questionnaires may not be limited.

The storage unit 40 may store the answer of the questionnaire and accumulate the answer information each time when the answer of the questionnaire is made a plurality of times. The statistical processing unit 44 may take statistics by using questionnaire responses as statistical data (for example, popular cosmetics, skin quality, etc.). The statistical processing unit 44 may store statistical data in the storage unit 40. The output unit 52 may create a report with reference to statistical data stored in the storage unit 40. For example, the output unit 52 refers to statistical data stored in the storage unit 40, and is suitable for a cosmetic product that is popular among those who have the same skin quality and / or who has the same skin quality in a report to be created. You may try to introduce cosmetics that you think you have.

It should be noted that the questionnaire items may have different questionnaire items depending on the number of times the target person has answered the questionnaire. As an example, the storage unit 40 stores the number of questionnaires of the target person. The statistical processing unit 44 refers to the storage unit 40 and creates the next questionnaire item based on the number of questionnaires, the answer, and the analysis result. When the number of questionnaires is five and there are three answers that indicate “not satisfied with cosmetics in use”, a questionnaire item that asks “trial period of cosmetics in use” is created from the analysis result. If the subject is made to answer the questionnaire items created in this way at the time of the next order or the like, more appropriate skin care advice can be provided for each subject.

Further, the storage unit 40 may store and accumulate data corresponding to the questionnaire items. For example, the storage unit 40 stores and accumulates the used cosmetic information according to the age group, the residential area, the occupation, and the analysis result from the answer of the first item shown in FIG. The statistical processing unit 44 refers to the storage unit 40 and calculates the statistics of the cosmetics used for each age group, each residential area, each occupation, and each analysis result as statistical data. The statistical processing unit 44 stores the statistical data in the storage unit 40. The output unit 52 describes the statistical data stored in the storage unit 40 in the report. According to this, the target person can be made aware of popular cosmetics for each age group, each residential area, each occupation, and each analysis result.

The storage unit 40 stores and accumulates the skin quality (for example, smooth, dry, etc.) that the subject feels from the answer of the second item, for example. The statistical processing unit 44 refers to the storage unit 40 and calculates a change in skin quality felt by the subject as statistical data. Specifically, how long the same answer continues or how long the same answer lasts is calculated. When the calculation result is larger than a predetermined value, the statistical processing unit 44 determines whether the cosmetic in use matches or does not match the subject's skin according to the answer. The statistical processing unit 44 stores the determination result in the storage unit 40 together with the statistical data.

The operator of the skin condition analysis system 10 can grasp whether or not appropriate advice can be provided to the target person by referring to the determination result stored in the storage unit 40. If the operator does not give appropriate advice to the target person, that is, there are many judgments that do not fit the target person's skin, the advice algorithm is improved to provide the target person with appropriate advice. I can do it. Therefore, the quality of advice in skin care in the analyzer 30 can be further improved.

The storage unit 40 stores, for example, data on customer satisfaction in the cosmetics in use from the answer of the third item. The statistical processing unit 44 refers to the storage unit 40 and calculates statistical data of cosmetics with high customer satisfaction. Specifically, it calculates how many answers with high customer satisfaction are continuous or how long the same answer lasts. When the calculation result is smaller than a predetermined value, the statistical processing unit 44 determines that the cosmetic in use does not match the subject's skin according to the answer to the questionnaire. The statistical processing unit 44 stores the determination result in the storage unit 40 together with the statistical data. Based on the determination result stored in the storage unit 40, the output unit 52 describes the information providing website for selecting cosmetics and / or skin care suitable for the subject's skin in the report, and the cosmetics suitable for the subject's skin. And / or an informational website for selecting skin care can be introduced to the subject.

The storage unit 40 stores, for example, data of customer dissatisfaction with the cosmetics in use from the answer of the fourth item, and accumulates the data. The statistical processing unit 44 refers to the storage unit 40 and calculates statistical data of cosmetics with a high degree of customer dissatisfaction. Specifically, it calculates how many responses with high customer dissatisfaction level are continuous or how long the same response continues. When the calculation result is larger than a predetermined value, the statistical processing unit 44 stores the calculation data in the storage unit 40 together with the answer of the first item. The output unit 52 can create a report based on the calculated data and provide the report to a cosmetic manufacturer. As a result, the cosmetic manufacturer can develop and / or improve cosmetics that meet the needs of consumers.

The storage unit 40 stores and accumulates points (for example, price, quality, etc.) that are important when the target person purchases cosmetics from the answer of the fifth item, for example. The statistical processing unit 44 refers to the storage unit 40, takes statistics of the answered important points, and calculates the statistical data. The statistical processing unit 44 stores the calculated statistical data in the storage unit 40. The output unit 52 refers to the statistical data stored in the storage unit 40, and creates a report describing recommended cosmetic information according to the wishes of the target person together with the analysis result. Thereby, the skin condition analysis system 10 can provide cosmetic information in line with the request of the subject.

The storage unit 40 stores and accumulates data on lifestyle habits of the subject (for example, work shifts, meal contents, etc.) from the answer of the sixth item, for example. The statistical processing unit 44 refers to the storage unit 40, takes statistics on the lifestyle habits that have been answered, and calculates the statistical data. The statistical processing unit 44 stores the calculated statistical data in the storage unit 40. The output unit 52 refers to the statistical data stored in the storage unit 40, and in addition to the analysis results, provides detailed skin care advice for people who frequently work night shifts, skin care advice according to dietary habits, etc. Advice can be provided.

The storage unit 40 may further store history data having a plurality of sets including at least one of the subject's actual age, skin texture index value, and skin age for one subject. The history processing unit 46 stores at least one of the latest skin texture index value and skin age, and history data of at least one of the previous skin texture index value and skin age (for example, the skin texture index value and skin age from the first time to the previous time). ) And the age of the subject to which the skin condition has improved is calculated, and the calculated history data is stored in the storage unit 40. The history processing unit 46 may further refer to the history data stored in the storage unit 40 and cause the output unit 52 to output the calculated history data. Thereby, the skin condition analysis system 10 can make the subject recognize how much his skin was rejuvenated with respect to the actual age by presenting the history data to the subject.

Further, the history processing unit 46 may cause the output unit 52 to output advice such as introducing cosmetics that match the skin rather than the currently used cosmetics based on the calculated history data. Thereby, the skin condition analysis system 10 can make the subject maintain motivation for skin care.

Further, the storage unit 40 may store a set including at least one of the actual age of the subject, a questionnaire result regarding the subject's skin, and a skin texture index value and skin age. The damage factor analysis unit 48 manages the subject's skin based on the questionnaire results stored in the storage unit 40 and the subject's lifestyle (for example, length of sleep time, eating habits, drinking alcohol, smoking, cosmetics in use, etc. ) Analyzing damage factors (for example, short sleep time, uneven eating habits, alcohol consumption, amount of smoking, cosmetic ingredients in use, etc.) to be given to the skin every time, and storing the analyzed damage factors in the storage unit 40 To do. The damage factor analysis unit 48 may further refer to the damage factor stored in the storage unit 40 and cause the output unit 52 to output the analyzed damage factor. Thereby, the skin condition analysis system 10 can promote the rejuvenation of the skin by improving the damage factor to the subject by presenting the damage factor to the subject.

Moreover, the memory | storage part 40 may store the group containing at least one of the subject's real age, the questionnaire result regarding the subject's skin, the cosmetics used by the subject, the skin texture index value, and the skin age. . The cosmetic selection unit 50 selects cosmetics that improve the skin condition for each characteristic of the subject's skin based on the questionnaire results stored in the storage unit 40. The cosmetic selection unit 50 selects, for example, a cosmetic for a person with a large amount of smoking for a person with a large amount of smoking (for example, a person who smokes one or more boxes per day), For the person who smokes, cosmetics for people with a small amount of smoking may be selected. Further, the cosmetic product selection unit 50 may select a cosmetic product suitable for a subject whose skin is not damaged and whose current damage is easy to recover for those whose skin is damaged by the cosmetic product in use.

Specifically, the cosmetic selection unit 50 refers to cosmetic data stored in the storage unit 40 (for example, data in which recommended cosmetics are associated with each damage factor such as the amount of smoking) and recommends Choose cosmetics. The output unit 52 may cause the output unit 52 to output the cosmetic selected by the cosmetic selection unit 50 as a report. Thereby, the skin condition analysis system 10 can present the recommended cosmetics to the subject for each characteristic of the subject's skin, and thus can promote rejuvenation of the subject's skin.

FIG. 10 shows an example of a report created by the output unit 52 according to the present embodiment. The report is generated by the output unit 52 according to the report format obtained from the report format (model) stored in the storage unit 40. The report describes the skin age analysis result and the moisturizing analysis result. In the skin age analysis result, the skin texture index value scale is placed at the center according to the report format, and the skin texture analysis skin image corresponding to the subject's actual age is placed on the left side of the scale. On the right side, the skin image for skin texture analysis used in the subject's current analysis is arranged. The skin image for skin texture analysis corresponding to the subject's actual age and the skin image for skin texture analysis used in the subject's current analysis are acquired from the storage unit 40.

The output unit 52 further acquires the skin texture index value stored in the storage unit 40 and acquires the skin texture index value associated with the skin image for skin texture analysis corresponding to the actual age of the subject. . The output unit 52 arranges triangular icons on both sides of the scale based on these skin texture index values. The left icon indicates the skin texture index value of the skin image corresponding to the actual age, and the right icon indicates the skin texture index value of the skin image for skin texture analysis used in this analysis. Thereby, the subject can visually grasp whether the texture of his / her skin is fine or rough with respect to the texture of the skin of real age.

The skin image for comparison displayed on the left side may be the skin image used in the previous analysis of the subject. The output unit 52 also acquires the skin image used in the previous analysis of the subject from the storage unit 40. In this case, since it is possible to visually grasp how much improvement has been seen compared to the previous time, the target person can visually grasp the degree of the effect of the cosmetics currently in use. The comparison target skin image displayed on the left side may be a reference skin image with a limited area. The output unit 52 also acquires a reference skin image with a limited area from the storage unit 40. In this case, for example, when the region is limited to Japan, the subject can know how fine or rough his / her skin texture is compared to the average Japanese skin texture of the same age. it can.

In the comment column located below the skin age analysis result, a comment corresponding to the current skin age analysis result is described. The output unit 52 selects an appropriate comment from the comment data stored in advance in the storage unit 40 based on the statistical data stored in the storage unit 40 by the statistical processing unit 44, and selects the selected comment in the comment field. It describes. The comment content includes, for example, advice for improving the skin texture index value based on the analysis data. Specifically, if the skin texture index value of a subject whose actual age is 32 years old is "10", "Your skin texture is the texture of skin that is 10 years younger than the actual age. By refraining from smoking, you can get closer to rejuvenating skin with your current cosmetics. " The comment data stored in the storage unit 40 may be updated as needed by the operator of the skin condition analysis system 10.

The advice may be a comparison with the previous skin age analysis result. The output unit 52 compares the previous skin age analysis result and the current skin age analysis result (for example, compares skin texture index values) based on the statistical data stored in the storage unit 40 by the statistical processing unit 44. If there is a difference in the comparison result, an appropriate comment is selected from the comment data stored in advance in the storage unit 40 according to the difference, and the selected comment is written in the comment field. Further, the output unit 52 uses, for example, a skin texture index as a content corresponding to a change in the skin texture index value of the subject person based on the statistical data stored in the storage unit 40 by the statistical processing unit 44, for example, than a predetermined threshold. If the change in value is scarce, make the cosmetic selection section 50 select cosmetics that can be recommended in addition to existing cosmetics, and enter recommended cosmetic information in the comment field. May be.

Further, the output unit 52 may write information that is good for skin texture in the comment column based on the unique information of the subject stored in the storage unit 40 by the statistical processing unit 44. For example, the output unit 52 generates regional special foods that are recommended for the skin texture from the regional information of the subject based on the specific information and statistical data of the subject stored in the storage unit 40 by the statistical processing unit 44. It may be described in the comment column. Moreover, you may write the advice according to the skin age analysis result for every season of a subject in a comment column.

The skin moisturizing analysis result has a moisturizing index value scale at the center, the subject's previous skin image for moisturizing analysis is placed on the left side of the scale, and the right side of the scale is used for the subject's current analysis. The skin image for the moisturizing analysis was placed. The output unit 52 acquires the skin image for the previous moisture retention analysis of the subject and the skin image for the moisture retention analysis used for the current analysis of the subject from the storage unit 40. Further, the output unit 52 further acquires a moisturizing index value associated with the previous and current skin images for moisturizing analysis stored in the storage unit 40. The output unit 52 arranges triangular icons on both sides of the scale based on these moisturizing index values. The left icon indicates the moisture retention index value of the skin image for the previous moisture retention analysis, and the right icon indicates the moisture retention index value of the skin image for the moisture retention analysis used in the current analysis.

This allows the subject to visually grasp the current moisturizing state with respect to the previous moisturizing state. Note that the skin image to be compared displayed on the left side may be a skin image of the subject and the same trader. For example, the output unit 52 may detect other subjects of the same occupation with reference to the unique information in the storage unit 40, and may output the result of comparison with the moisturizing state of other subjects. In this case, for example, it is possible to know the possibility that moisturization will improve depending on skin care even in the same occupation, and to increase motivation for skin care.

In the comment column located below the skin moisturizing analysis result, a comment corresponding to the current skin moisturizing analysis result is described. The output unit 52 selects an appropriate comment from the comment data stored in advance in the storage unit 40 based on the statistical data stored in the storage unit 40 by the statistical processing unit 44, and selects the selected comment in the comment field. It describes. The comment content includes, for example, advice for improving the moisture retention index value based on the analysis data. Specifically, when the previous moisturizing index value is “6” and the current moisturizing index value is “9”, “the skin moisturizing state is much better than before. After bathing By taking care of, you can improve the moisturizing condition further. "

Also, the advice may be a comparison with the moisturizing index value before the previous time. Based on the statistical data stored in the storage unit 40 by the statistical processing unit 44, the output unit 52 has a change in the moisturizing index value, for example, as a content corresponding to the change in the moisturizing index value of the subject himself, for example, than a predetermined threshold. In the case where it is scarce, the cosmetic selection unit 50 may select cosmetics that can be recommended from cosmetics scheduled to be released soon in addition to the existing cosmetics, and the cosmetic information recommended for the target person may be described in the comment column.

Further, the output unit 52 may describe information that is good for moisturizing the skin in the comment column based on the specific information of the subject stored in the storage unit 40 by the statistical processing unit 44. For example, the output unit 52 uses the local information of the subject stored in the storage unit 40 by the statistical processing unit 44 and the statistical data to obtain regional special foods that are recommended for moisturizing the skin. It may be described in the comment column. Further, advice according to the skin moisturizing analysis result of each season of the subject may be written in the comment column.

FIG. 11 shows an example of a hardware configuration of a computer 1900 according to this embodiment. A computer 1900 according to this embodiment is connected to a CPU peripheral unit having a CPU 2000, a RAM 2020, a graphic controller 2075, and a display device 2080 that are connected to each other by a host controller 2082, and to the host controller 2082 by an input / output controller 2084. Input / output unit having communication interface 2030, hard disk drive 2040, and CD-ROM drive 2060, and legacy input / output unit having ROM 2010, flexible disk drive 2050, and input / output chip 2070 connected to input / output controller 2084 With.

The host controller 2082 connects the RAM 2020 to the CPU 2000 and the graphic controller 2075 that access the RAM 2020 at a high transfer rate. The CPU 2000 operates based on programs stored in the ROM 2010 and the RAM 2020 and controls each unit. The graphic controller 2075 acquires image data generated by the CPU 2000 or the like on a frame buffer provided in the RAM 2020 and displays it on the display device 2080. Instead of this, the graphic controller 2075 may include a frame buffer for storing image data generated by the CPU 2000 or the like.

The input / output controller 2084 connects the host controller 2082 to the communication interface 2030, the hard disk drive 2040, and the CD-ROM drive 2060, which are relatively high-speed input / output devices. The communication interface 2030 communicates with other devices via a network. The hard disk drive 2040 stores programs and data used by the CPU 2000 in the computer 1900. The CD-ROM drive 2060 reads a program or data from the CD-ROM 2095 and provides it to the hard disk drive 2040 via the RAM 2020.

Also, the ROM 2010, the flexible disk drive 2050, and the relatively low-speed input / output device of the input / output chip 2070 are connected to the input / output controller 2084. The ROM 2010 stores a boot program that the computer 1900 executes at startup and / or a program that depends on the hardware of the computer 1900. The flexible disk drive 2050 reads a program or data from the flexible disk 2090 and provides it to the hard disk drive 2040 via the RAM 2020. The input / output chip 2070 connects the flexible disk drive 2050 to the input / output controller 2084 and inputs / outputs various input / output devices via, for example, a parallel port, a serial port, a keyboard port, a mouse port, and the like. Connect to controller 2084.

The program provided to the hard disk drive 2040 via the RAM 2020 is stored in a recording medium such as the flexible disk 2090, the CD-ROM 2095, or an IC card and provided by the user. The program is read from the recording medium, installed in the hard disk drive 2040 in the computer 1900 via the RAM 2020, and executed by the CPU 2000.

A program that is installed in the computer 1900 and causes the computer 1900 to function as the analysis device 30 includes a skin image selection module, a skin groove detection module, an index value calculation module, a skin age calculation module, a storage module, and a moisture retention detection module. A statistical processing module, a history processing module, a damage factor analysis module, and a cosmetic selection module. These programs or modules work on the CPU 2000 or the like to make the computer 1900 into the imaging unit 24, the skin image selection unit 32, the skin groove detection unit 34, the index value calculation unit 36, the skin age calculation unit 38, the storage unit 40, the moisturizing unit. The detection unit 42, the statistical processing unit 44, the history processing unit 46, the damage factor analysis unit 48, and the cosmetics selection unit 50 are caused to function.

The information processing described in these programs is read into the computer 1900, whereby the imaging unit 24, the skin image selection unit 32, the skin, which are specific means in which the software and the various hardware resources described above cooperate. It functions as a groove detection unit 34, an index value calculation unit 36, a skin age calculation unit 38, a storage unit 40, a moisture retention detection unit 42, a statistical processing unit 44, a history processing unit 46, a damage factor analysis unit 48, and a cosmetic selection unit 50. . And the specific analysis apparatus 30 according to the intended purpose is constructed | assembled by implement | achieving the calculation or processing of the information according to the intended purpose of the computer 1900 in this embodiment by these specific means.

As an example, when communication is performed between the computer 1900 and an external device or the like, the CPU 2000 executes a communication program loaded on the RAM 2020 and executes a communication interface based on the processing content described in the communication program. A communication process is instructed to 2030. Under the control of the CPU 2000, the communication interface 2030 reads transmission data stored in a transmission buffer area or the like provided on a storage device such as the RAM 2020, the hard disk drive 2040, the flexible disk 2090, or the CD-ROM 2095, and sends it to the network. The reception data transmitted or received from the network is written into a reception buffer area or the like provided on the storage device. As described above, the communication interface 2030 may transfer transmission / reception data to / from the storage device by a DMA (direct memory access) method. Instead, the CPU 2000 transfers the storage device or the communication interface 2030 as a transfer source. The transmission / reception data may be transferred by reading the data from the data and writing the data to the communication interface 2030 or the storage device of the transfer destination.

The CPU 2000 is all or necessary from among files or databases stored in an external storage device such as a hard disk drive 2040, a CD-ROM drive 2060 (CD-ROM 2095), and a flexible disk drive 2050 (flexible disk 2090). This portion is read into the RAM 2020 by DMA transfer or the like, and various processes are performed on the data on the RAM 2020. Then, CPU 2000 writes the processed data back to the external storage device by DMA transfer or the like. In such processing, since the RAM 2020 can be regarded as temporarily holding the contents of the external storage device, in the present embodiment, the RAM 2020 and the external storage device are collectively referred to as a memory, a storage unit, or a storage device. Various types of information such as various programs, data, tables, and databases in the present embodiment are stored on such a storage device and are subjected to information processing. Note that the CPU 2000 can also store a part of the RAM 2020 in the cache memory and perform reading and writing on the cache memory. Even in such a form, the cache memory bears a part of the function of the RAM 2020. Therefore, in the present embodiment, the cache memory is also included in the RAM 2020, the memory, and / or the storage device unless otherwise indicated. To do.

In addition, the CPU 2000 performs various operations, such as various operations, information processing, condition determination, information search / replacement, etc., described in the present embodiment, specified for the data read from the RAM 2020 by the instruction sequence of the program. Is written back to the RAM 2020. For example, when performing the condition determination, the CPU 2000 determines whether the various variables shown in the present embodiment satisfy the conditions such as large, small, above, below, equal, etc., compared to other variables or constants. When the condition is satisfied (or not satisfied), the program branches to a different instruction sequence or calls a subroutine.

Further, the CPU 2000 can search for information stored in a file or database in the storage device. For example, in the case where a plurality of entries in which the attribute value of the second attribute is associated with the attribute value of the first attribute are stored in the storage device, the CPU 2000 displays the plurality of entries stored in the storage device. The entry that matches the condition in which the attribute value of the first attribute is specified is retrieved, and the attribute value of the second attribute that is stored in the entry is read, thereby associating with the first attribute that satisfies the predetermined condition The attribute value of the specified second attribute can be obtained.

The program or module shown above may be stored in an external recording medium. As the recording medium, in addition to the flexible disk 2090 and the CD-ROM 2095, an optical recording medium such as DVD or CD, a magneto-optical recording medium such as MO, a tape medium, a semiconductor memory such as an IC card, and the like can be used. Further, a storage device such as a hard disk or RAM provided in a server system connected to a dedicated communication network or the Internet may be used as a recording medium, and the program may be provided to the computer 1900 via the network.

As mentioned above, although this invention was demonstrated using embodiment, the technical scope of this invention is not limited to the range as described in the said embodiment. It will be apparent to those skilled in the art that various modifications or improvements can be added to the above-described embodiment. It is apparent from the scope of the claims that the embodiments added with such changes or improvements can be included in the technical scope of the present invention.

The execution order of each process such as operations, procedures, steps, and stages in the apparatus, system, program, and method shown in the claims, the description, and the drawings is particularly “before” or “prior”. It should be noted that they can be implemented in any order unless the output of the previous process is used in the subsequent process. Regarding the operation flow in the claims, the description, and the drawings, even if it is described using “first”, “next”, etc. for the sake of convenience, it means that it is essential to carry out in this order. is not.

10 skin condition analysis system, 20 microscope, 22 lens unit, 24 imaging unit, 30 analysis device, 32 skin image selection unit, 34 skin groove detection unit, 36 index value calculation unit, 38 skin age calculation unit, 40 storage unit, 42 Moisturizing detection unit, 44 statistical processing unit, 46 history processing unit, 48 damage factor analysis unit, 50 cosmetic selection unit, 52 output unit, 100 sheet, 102 identification unit, 104 support unit, 106 sample collection unit, 108 adhesive protection unit, 120 containers, 122 lids, 124 storage units, 126 seals, 128 space sill units, 130, 132 storage spaces, 302, 304 primary lines, 306 secondary lines, 308 polygons, 1900 computers, 2000 CPU, 2010 ROM, 2020 RAM , 2030 communication interface, 2040 c Disk drives, 2050 flexible disk drive, 2060 CD-ROM drive, 2070 output chip, 2075 graphic controller, 2080 a display device, 2082 host controller 2084 output controller, 2090 a flexible disk, 2095 CD-ROM

Claims (18)

1. An analysis device for analyzing a skin image obtained by imaging the surface of the skin,
   A skin groove detection unit for detecting a line corresponding to the skin groove included in the skin image;
   An index value calculation unit for calculating an index value representing the skin state based on the arrangement state of the lines;
   An analysis apparatus comprising:
2. The analysis device according to claim 1, wherein the skin groove detection unit detects at least one of regularity of line arrangement and continuity of lines as an arrangement state of the lines.
3. The analysis device according to claim 1 or 2, wherein the skin groove detection unit detects a plurality of primary lines having a width satisfying a predetermined first reference width from the skin image and arranged in a grid pattern. .
4. The analysis device according to claim 3, wherein the skin groove detecting unit further detects a plurality of secondary lines extending between a plurality of primary lines and having a width satisfying a second reference width narrower than the first reference width.
5. 4. The analysis apparatus according to claim 3, wherein the index value calculation unit calculates the index value based on at least one of regularity of a plurality of primary lines and continuity of each primary line.
6. The analysis apparatus according to claim 4, wherein the index value calculation unit calculates the index value based on at least one of regularity of an array of secondary lines and continuity of each secondary line.
7. The index value calculation unit includes a first index value calculated based on at least one of the regularity of a plurality of primary lines and the continuity of each primary line, the regularity of the array of secondary lines, and each secondary The analysis apparatus according to claim 4, wherein the index value is calculated based on a second index value calculated based on at least one of line continuity.
8. The analysis apparatus according to claim 7, wherein the index value calculation unit calculates the index value further based on a size of a region surrounded by a plurality of primary lines and a plurality of secondary lines.
9. The analysis device according to any one of claims 1 to 8, further comprising a skin age calculation unit that calculates a skin age based on the index value.
10. The analysis apparatus according to claim 9, further comprising a storage unit that stores the actual age of the subject and at least one of the index value and the skin age corresponding to each of the plurality of subjects.
11. 11. The statistical processing unit according to claim 10, further comprising: a statistical processing unit that calculates, for each of the index values stored in the storage unit, statistical data of a subject's actual age that is analyzed as having the index value. Analysis device.
12. The storage unit stores, for one subject, history data having a plurality of sets including the subject's actual age and at least one of the index value and the skin age,
    Based on the result of comparing the historical data of at least one of the latest index value and skin age with the previous index value and / or skin age, to which age of the subject the skin condition has improved The analysis device according to claim 10 or 11, further comprising a history processing unit for calculating the value.
13. The storage unit stores a set including at least one of a subject's actual age, a questionnaire result regarding the subject's skin, and an index value and skin age,
    The analysis device according to any one of claims 10 to 12, further comprising a damage factor analysis unit that analyzes a damage factor given to the skin for each of the management of the subject's skin based on the questionnaire result and the lifestyle of the subject.
14. A skin sample collection kit for collecting a sample of the surface of the skin to be analyzed by the analysis device according to any one of claims 1 to 13,
    An analysis solution applied to the surface of the skin and dried and solidified;
    A sheet for adhering the dried analysis solution;
    A skin sample collection kit.
15. The skin sample collection kit according to claim 14, wherein the analysis solution does not contain cyanoacrylate.
16. A container for storing the sheet adhered with the dried analysis solution;
    The skin sample collection kit according to claim 14 or 15, wherein the container has a storage space for storing the sheet.
17. A program for causing a computer to function as the analysis device according to any one of claims 1 to 13.
18. An analysis method for analyzing a skin image obtained by imaging a skin surface,
    A skin groove detection step of detecting a line corresponding to the skin groove included in the skin image;
    An index value calculating step for calculating an index value representing a skin state based on the arrangement state of the lines;
    An analysis method comprising:

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