CN108520280A - A kind of bulk commodity charge system based on machine vision - Google Patents
A kind of bulk commodity charge system based on machine vision Download PDFInfo
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- CN108520280A CN108520280A CN201810327328.2A CN201810327328A CN108520280A CN 108520280 A CN108520280 A CN 108520280A CN 201810327328 A CN201810327328 A CN 201810327328A CN 108520280 A CN108520280 A CN 108520280A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/24—Classification techniques
- G06F18/241—Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches
- G06F18/2413—Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches based on distances to training or reference patterns
- G06F18/24147—Distances to closest patterns, e.g. nearest neighbour classification
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01G—WEIGHING
- G01G19/00—Weighing apparatus or methods adapted for special purposes not provided for in the preceding groups
- G01G19/40—Weighing apparatus or methods adapted for special purposes not provided for in the preceding groups with provisions for indicating, recording, or computing price or other quantities dependent on the weight
- G01G19/413—Weighing apparatus or methods adapted for special purposes not provided for in the preceding groups with provisions for indicating, recording, or computing price or other quantities dependent on the weight using electromechanical or electronic computing means
- G01G19/414—Weighing apparatus or methods adapted for special purposes not provided for in the preceding groups with provisions for indicating, recording, or computing price or other quantities dependent on the weight using electromechanical or electronic computing means using electronic computing means only
- G01G19/415—Weighing apparatus or methods adapted for special purposes not provided for in the preceding groups with provisions for indicating, recording, or computing price or other quantities dependent on the weight using electromechanical or electronic computing means using electronic computing means only combined with recording means
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- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/40—Extraction of image or video features
- G06V10/44—Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersections; Connectivity analysis, e.g. of connected components
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/40—Extraction of image or video features
- G06V10/48—Extraction of image or video features by mapping characteristic values of the pattern into a parameter space, e.g. Hough transformation
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Abstract
A kind of bulk commodity charge system based on machine vision：Including photographing module；Image processing module；Identification module；Charging module；Output module.The beneficial effects of the invention are as follows：It is identified based on closest template matching algorithm, Database is convenient, only needs single sample.Bulk commodity charge system based on machine vision, reduces the step of being manually entered type of merchandize, instead Machine Vision Recognition type of merchandize and quantity, and is sent to charging module according to communication protocol, completes charging.For businessman, reduce human cost and customer's queuing time；For staff, reduce cumbersome uninteresting labour；For consumer, consumption time has been saved, has optimized consumption experience.
Description
Technical field
The present invention relates to field of artificial intelligence, specially a kind of bulk commodity charge system based on machine vision.
Background technology
Due to being difficult to directly stamp price tag on bulk commodity, such as apple, rice, bulk commodity meter at present
Take, needs to arrange for staff and identify type of merchandize and input computer charging, consumer needs to wait in line, and expends in the extreme
Time and efforts.Businessman's human cost is high, and staff is cumbersome, and consumer's time cost is high, experience is poor.With artificial intelligence
The every aspect that energy technology enters life can be reduced using Machine Vision Recognition type of merchandize or quantity and be manually entered commodity
The step of type, and it is sent to charging module according to communication protocol, export price information completes charging.For businessman, reduce
Human cost and customer's queuing time；For staff, reduce cumbersome uninteresting labour；For consumer, saves and disappeared
It is time-consuming, optimize consumption experience.
Invention content
To solve the above problems, the present invention provides a kind of bulk commodity charge system based on machine vision.
Technical scheme of the present invention is specially：
A kind of bulk commodity charge system based on machine vision：Including photographing module, pass through camera lens, light source and camera handle
The optical image of bulk commodity is converted to digital signal image；Image processing module, to the digital signaling diagram of photographing module shooting
As carrying out image segmentation and feature extraction；Identification module is based on closest template matching algorithm, identification image processing module processing
Data afterwards identify the species characteristic and quantity of bulk commodity；Charging module, the bulk commodity identified according to identification module
Type charging is completed according to the type of merchandize unit price of storage and the commodity weight or quantity；Output module, output type of merchandize,
Unit price, weight or quantity and total price information.
Further：The photographing module includes camera lens, camera and light source.
Further：The camera uses digital camera.
Further：Also there is Merchandise Template property data base, Merchandise Template property data base to be connect with identification module.
Further：Image processing module carries out feature extraction using PCA-SIFT methods.
Further：Identification module, using closest template matching algorithm, identify bulk commodity species characteristic or
Quantity.
Further：Image processing module carries out edge detection using Canny detection methods.
Further：Image processing module carries out edge detection using Hough transform detection method.
Compared with prior art, the beneficial effects of the invention are as follows：It is identified based on closest template matching algorithm, data
It is convenient that library is established, and only needs single sample.Bulk commodity charge system based on machine vision, reduces and is manually entered type of merchandize
The step of, instead Machine Vision Recognition type of merchandize and quantity, and it is sent to charging module according to communication protocol, complete meter
Take.For businessman, reduce human cost and customer's queuing time；For staff, reduce cumbersome uninteresting labour；It is right
In consumer, consumption time has been saved, has optimized consumption experience.
Description of the drawings
Fig. 1 is that a kind of structure diagram of bulk commodity charge system based on machine vision of the present invention (is suitable for by kind
The commodity that class sum number gauge takes).
Fig. 2 is that a kind of structure diagram of bulk commodity charge system based on machine vision of the present invention (is suitable for by kind
The commodity of class and weight charging).
Specific implementation mode
Embodiment 1：
A kind of bulk commodity charge system based on machine vision, including photographing module (1), pass through camera lens, light source and phase
The optical image of bulk commodity is converted to digital signal image by machine, and image processing module (2) carries out figure to digital signal pattern
As segmentation and feature extraction, the wherein use PCA-SIFT methods of feature extraction, identification module (3) is based on closest template
With algorithm, identify that the species characteristic or quantity of bulk commodity, communication module (4) are sent to type number information and weigh
Module is sent to charging module, charging module the weight information obtained from Weighing module, or type and quantity information
(5), charging is completed according to type unit price and weight or quantity, output module (6), output class, unit price, weight or quantity and total
Valence information confirms for consumer, completes charging.
Such as the above-mentioned bulk commodity charge system based on machine vision, concrete principle and feature are as follows：
(1) optical image of bulk commodity is converted into digital signaling diagram by photographing module by light source, camera lens and camera
Picture：Light source illuminates target, improves brightness so that camera lens collects image with distinct contrast, causes the effect for being conducive to image procossing
Fruit.Shots are irradiated the reflected light of commodity by light source, and focus on the photosurface of imaging sensor of camera.Camera
CCD (Charge Coupled Device) or CMOS (Complementary Metal Oxide Semiconductor) image
Optical image is converted into digital signal image by sensor by opto-electronic conversion, charge storage, electric charge transfer and signal-obtaining, and
Send image processing module to.
(2) image processing module carries out image segmentation and feature extraction to digital signal pattern：According to each position of image
RGB color and edge, edge detection is detected using Canny or Hough transform detection, divides the image into different regions.
According to color and edge bulk commodity and shopping bag and background separation come.Feature extraction is from the region in bulk split
In, using PCA-SIFT methods, extract the crucial point feature of bulk commodity.
(3) identification module automatically identifies the species characteristic or number of bulk commodity using closest template matching algorithm
Amount：The feature of extraction is matched with the template characteristic of the extensive stock stored in database.Template T (m, n) in feature
The subgraph S covered in figureijThe aberration of (m, n) is:
First item is the energy of subgraph in formula, and (i, j) is characterized image vegetarian refreshments coordinate, and (m, n) is template pixel point coordinates.
Section 3 is the energy of template, all unrelated with template matches.Section 2 is that template is related each other to subgraph, is changed with (i, j)
Become.When template and subgraph match, this is by maximum value.After being normalized, the related coefficient of template matches is obtained：
When template and just the same subgraph, coefficient R (i, j)=1.After all search being completed in searched figure S,
Find out the maximum value Rmax (i, j) of R, corresponding subgraph Sij(m, n) is to match target, and type is determined with this.And big Mr. Yu
The quantity of one threshold value as matches the quantity of target.
(4) communication module carries out data communication protocol conversion, type and quantity to identification module, charging module data
Information is sent to charging module：By network interface or serial ports (including USB port), the type of bulk commodity is compiled according to communication protocol
Number, quantity information be sent to charging module.By reserved external communication interface, Merchandise Template property data base is updated
It is read out with to identification module, charging module, Weighing module data.
(5) charging module completes charging according to type unit price and weight or quantity：Total price=unit price × weight, Huo Zhezong
Valence=unit price 1 × quantity 1+ unit price 2 × quantity 2+ 3 × quantity of unit price 3+ ....
(6) output module, output class, unit price, weight or quantity and total price information confirm for consumer, complete charging：
Pass through printing device printing or display screen display of commodity label bar code and type, unit price, weight or quantity and total price information.
Embodiment 2：
A kind of bulk commodity charge system based on machine vision, can also increase Weighing module, Weighing module is identified
The weight of bulk commodity is weighed after the type of merchandize information of module identification, and weight information is sent to charging module.
Weighing module is communicated by communication module and identification module, charging module.
Communication module, symmetrical weight module data carry out data communication protocol conversion, type number information are sent to and is weighed
Module, the weight information obtained from Weighing module, by network interface or serial ports (including USB port), according to communication protocol in bulk
The type number of commodity, weight information are sent to charging module.
Specific work process：
As shown in Figure 1, when being settled accounts with chafing dish restaurant, for the bamboo stick by type and quantity charging, after consumer completes feed,
Waiter tiles bamboo stick and be intensively placed on certain on dining table starts billing operation with mobile phone open charge system.Through
Light source, i.e. mobile phone flashlight irradiate, lens focus, and the camera in camera module is converted to bamboo stick and appendicular shadow signal
Digital signal image, and it is sent to image processing module.Image processing module is according to the RGB color and edge of bamboo stick, edge inspection
It surveys and is detected using Hough transform, divide the image into different regions, and isolate the region where bamboo stick.Using PCA-
SIFT methods extract product features.Identification module by with each template matches in bulk commodity database, confirm bamboo stick
Type and quantity, and type number information and quantity information are sent to by communication module by charging module, charging module according to
Information transfers the unit price of food representated by various bamboo sticks, and according to quantity information, according to formula：Total price=unit price 1 × number
1+ unit price 2 × quantity 2+ unit price 3 × quantity 3+ ... are measured, total price is calculated.Output module shows various bamboos on mobile phone screen
Label represent unit price, quantity and the total price information of food.After consumer watches confirmation, charging is completed.
As shown in Fig. 2, by taking supermarket's certain apple for sale as an example, after consumer chooses, it is placed on charge system region, is passed through
Light source irradiates, lens focus, and the appendicular shadow signal of apple and periphery is converted to digital signal by the camera in camera module
Image, and it is sent to image processing module.Image processing module presses commodity, residual leaf, the plastic shopping bag and background for filling commodity
According to the RGB color and edge at each position, edge detection is detected using Canny, divides the image into different regions.And it isolates
Region where commodity.Product features are extracted using PCA-SIFT methods.Identification module by in bulk commodity database
Each template matches calculate the matching related coefficient 0.99 with certain apple template, are maximum value.Confirm that selected commodity are certain
Kind apple, and type number information is sent to communication module.Communication module and Weighing module are through network interface or serial ports (including USB
Mouthful) interaction, the weight information of apple is obtained, information and weight information are then sent to charging module, charging module root
The unit price of certain apple is transferred according to information, and calculates total price according to weight information.The printing device of output module prints
The label bar code and type of certain apple of label, unit price, weight and total price information are affixed on shopping and take after consumer confirms, complete
At charging.
As shown in Fig. 2, by taking supermarket's certain rice for sale as an example, after consumer chooses, it is placed on charge system region, is passed through
Light source irradiates, lens focus, and the appendicular shadow signal of rice and periphery is converted to digital signal by the camera in camera module
Image, and it is sent to image processing module.Image processing module presses commodity, residual leaf, the plastic shopping bag and background for filling commodity
According to the RGB color and edge at each position, edge detection is detected using Canny, divides the image into different regions.And it isolates
Region where commodity.Product features are extracted using PCA-SIFT methods.Identification module by in bulk commodity database
Each template matches calculate the matching related coefficient 0.97 with certain rice template, are maximum value.Confirm that selected commodity are certain
Kind rice, and type number information is sent to communication module.Communication module and Weighing module are through network interface or serial ports (including USB
Mouthful) interaction, the weight information of rice is obtained, information and weight information are then sent to charging module, charging module root
The unit price of certain rice is transferred according to information, and calculates total price according to weight information.The printing device of output module prints
The label bar code and type of certain rice of label, unit price, weight and total price information are affixed on shopping and take after consumer confirms, complete
At charging.
The present invention reduces type of merchandize is manually entered, instead Machine Vision Recognition type of merchandize or quantity,
And charging module is sent to by communication protocol, complete charging.For businessman, reduce human cost and customer's queuing time；
For staff, reduce cumbersome uninteresting labour；For consumer, consumption time has been saved, has optimized consumption experience.Quotient
Family, staff, consumer have nothing in common with each other the benefit of degree, and charging process is more intelligent, is a kind of very promising charging
System.
What has been described above is only a preferred embodiment of the present invention, it is noted that for those skilled in the art,
Under the premise of not departing from general idea of the present invention, several changes and improvements can also be made, these should also be considered as the present invention's
Protection domain.
Claims (8)
1. a kind of bulk commodity charge system based on machine vision, it is characterised in that：Including photographing module, pass through camera lens, light
The optical image of bulk commodity is converted to digital signal image by source and camera；Image processing module, to photographing module shooting
Digital signal image carries out image segmentation and feature extraction；Identification module is based on closest template matching algorithm, identifies at image
The data after resume module are managed, identify the species characteristic and quantity of bulk commodity；Charging module is identified according to identification module
The type of bulk commodity charging is completed according to the type of merchandize unit price of storage and the commodity weight or quantity；Output module, it is defeated
Go out type of merchandize, unit price, weight or quantity and total price information.
2. a kind of bulk commodity charge system based on machine vision as described in claim 1, it is characterised in that：The camera shooting
Module includes camera lens, camera and light source.
3. a kind of bulk commodity charge system based on machine vision as claimed in claim 2, it is characterised in that：The camera
Use digital camera.
4. a kind of bulk commodity charge system based on machine vision as described in claim 1, it is characterised in that：Also there is quotient
Product template characteristic database, Merchandise Template property data base are connect with identification module.
5. a kind of bulk commodity charge system based on machine vision as described in claim 1, it is characterised in that：Image procossing
Module carries out feature extraction using PCA-SIFT methods.
6. a kind of bulk commodity charge system based on machine vision as described in claim 1, it is characterised in that：Identify mould
Block identifies the species characteristic or quantity of bulk commodity using closest template matching algorithm.
7. a kind of bulk commodity charge system based on machine vision as described in claim 1, it is characterised in that：Image procossing
Module carries out edge detection using Canny detection methods.
8. a kind of bulk commodity charge system based on machine vision as described in claim 1, it is characterised in that：Image procossing
Module carries out edge detection using Hough transform detection method.
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| CN201810327328.2A CN108520280A (en) | 2018-04-12 | 2018-04-12 | A kind of bulk commodity charge system based on machine vision |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111967942A (en) * | 2020-08-20 | 2020-11-20 | 渭南双盈未来科技有限公司 | Intelligent shopping method |
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| US20010027428A1 (en) * | 2000-04-04 | 2001-10-04 | Nec Corporation | Network settlement system and method |
| CN107767590A (en) * | 2016-08-16 | 2018-03-06 | 深圳仪普生科技有限公司 | Automatic identification commercialization bar code electronic scale and Automatic identification method |
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Inventor after: Wang Yunfei Inventor after: Zhang Liyan Inventor after: Kong Yijun Inventor after: Zhang Chunli Inventor after: Gao Yingbo Inventor after: Yue Zongping Inventor after: Ma Junjie Inventor after: Meng Xiangwei Inventor before: Wang Yunfei Inventor before: Zhu Xiangbo Inventor before: Mao Wenxin Inventor before: Xue Weijie Inventor before: Zhang Liyan Inventor before: Meng Yinna Inventor before: Yan Jianbing Inventor before: Zhang Chunli Inventor before: Duan Chaolei Inventor before: Zhao Weiwei |
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