JP5075946B2 - Pattern inspection apparatus and pattern inspection method - Google Patents

Description

  Embodiments described herein relate generally to a pattern inspection apparatus and a pattern inspection method.

  In recent years, the circuit line width required for a semiconductor element has been increasingly narrowed as a large scale integrated circuit (LSI) is highly integrated and has a large capacity. These semiconductor elements use an original pattern pattern (also referred to as a mask or a reticle, hereinafter referred to as a mask) on which a circuit pattern is formed, and the pattern is exposed and transferred onto a wafer by a reduction projection exposure apparatus called a stepper. It is manufactured by forming a circuit. Therefore, a pattern drawing apparatus capable of drawing a fine circuit pattern is used for manufacturing a mask for transferring such a fine circuit pattern onto a wafer. A pattern circuit may be directly drawn on a wafer using such a pattern drawing apparatus. Alternatively, development of a laser beam drawing apparatus for drawing using a laser beam in addition to an electron beam has been attempted.

  In addition, improvement in yield is indispensable for manufacturing an LSI that requires a large amount of manufacturing cost. However, as represented by a 1 gigabit class DRAM (Random Access Memory), the pattern constituting the LSI is about to be in the order of submicron to nanometer. One of the major factors that reduce the yield is a pattern defect of a mask used when an ultrafine pattern is exposed and transferred onto a semiconductor wafer by a photolithography technique. In recent years, with the miniaturization of LSI pattern dimensions formed on semiconductor wafers, the dimensions that must be detected as pattern defects have become extremely small. Therefore, it is necessary to improve the accuracy of a pattern inspection apparatus that inspects defects in a transfer mask used in LSI manufacturing.

  On the other hand, with the development of multimedia, LCDs (Liquid Crystal Display) are increasing in size of the liquid crystal substrate to 500 mm × 600 mm or more, and TFTs (Thin Film Transistors) formed on the liquid crystal substrate. : Thin film transistors) and the like are being miniaturized. Therefore, it is required to inspect a very small pattern defect over a wide range. For this reason, there is an urgent need to develop a sample inspection apparatus for efficiently inspecting defects of a photomask used in manufacturing such a large area LCD pattern and a large area LCD in a short time.

  Here, in a conventional pattern inspection apparatus, an optical image obtained by imaging a pattern formed on a sample such as a lithography mask using a magnifying optical system at a predetermined magnification and an identical pattern on the sample are captured. It is known to perform an inspection by comparing with an optical image. For example, as a pattern inspection method, a “die to die inspection” that compares optical image data obtained by imaging the same pattern at different locations on the same mask, or a drawing apparatus that draws a pattern using pattern-designed CAD data as a mask Drawing data (design pattern data) converted into a device input format for input to the inspection device is input to the inspection device, design image data (reference image) is generated based on the drawing data, and measurement data obtained by imaging the pattern There is a “die to database test” that compares an optical image. In the inspection method in such an inspection apparatus, the sample is placed on the stage, and the stage is moved so that the light beam scans on the sample and the inspection is performed. The sample is irradiated with a light beam by a light source and an illumination optical system. The light transmitted or reflected by the sample is imaged on the sensor via the optical system. The image picked up by the sensor is sent to the comparison circuit as measurement data. The comparison circuit compares the measurement data and the reference data according to an appropriate algorithm after the alignment of the images, and determines that there is a pattern defect if the shape and the output signal level do not match.

  Inspection apparatuses for semiconductor patterns such as masks and wafers are required to detect fine defects on a semiconductor pattern with high resolution. In an apparatus for inspecting an optical image using a semiconductor pattern inspection apparatus, a sensor using a solid-state image sensor such as a line sensor, an area sensor, or a TDI (Time Delay Integration) sensor is used. An enlarged optical image of the pattern is formed on the sensor by an optical system, and an electrical image signal obtained by the sensor is processed and measured and inspected.

  Here, it has been confirmed that the signal amplitude of the pattern, that is, the contrast rapidly decreases in the mask in which the isolated line or the so-called line and space (L / S) pattern is formed as the semiconductor pattern is miniaturized. For example, an L / S pattern having a wiring width of 100 nm or less in an EUV mask that is exposed to a wafer at a wavelength of 13.5 nm may be used. If the contrast of the picked-up optical image is low, the resolution of the image is low and it is difficult to realize a highly sensitive inspection. Therefore, it is required to increase the contrast of the output data from the sensor. However, conventionally, a method for sufficiently solving such a problem has not been established.

“Novel EUV mask inspection tool with 199-nm laser source and high-resolution optics”, SPIE Vol 7488.

  An embodiment of the present invention overcomes the above-described problems, and an apparatus capable of obtaining sufficient contrast necessary for inspection even when inspecting a mask on which a pattern having a reduced signal amplitude is formed, and It aims to provide a method.

According to the embodiment, the pattern inspection apparatus includes a sensor, a storage device, a gradation conversion unit, and a comparison unit. Such a sensor captures an optical image of the patterned mask to be inspected. The storage device stores a plurality of gradation conversion tables created according to the mask type. The gradation conversion unit selects a gradation conversion table corresponding to the type of the mask to be inspected from a plurality of gradation conversion tables stored in the storage device, and the gradation conversion table selects the gradation conversion table corresponding to the selected gradation conversion table. The pixel value of the optical image data picked up by the sensor is subjected to gradation conversion. The comparison unit inputs reference image data to be compared with optical image data subjected to gradation conversion, and compares the optical image data subjected to gradation conversion with the reference image data for each pixel. In the plurality of gradation conversion tables, a change degree for gradation conversion according to a gradation value or a gradation region is variably created,
The comparison unit selectively uses a plurality of thresholds according to the gradation value or the gradation region when comparing,
The reference image data is gradation-converted at the same gradation conversion table ratio as the optical image data,
Based on the gradation level indicated by the reference data, for each pixel, it is determined whether the gradation value of the reference data is a gradation area where the gradation resolution is increased or a gradation area where the gradation resolution is reduced in the optical image data. Is done.

In addition, according to the embodiment, the pattern inspection method includes a step in which a sensor captures an optical image of a patterned mask to be inspected, and a storage device that stores a plurality of gradation conversion tables created according to the mask type A gradation conversion table corresponding to the type of the mask to be inspected is selected from a plurality of gradation conversion tables stored in the table, and optical image data captured by the sensor along the selected gradation conversion table is selected. The step of converting the gradation of the pixel value and the reference image data to be compared with the optical image data subjected to the gradation conversion are input, and the optical image data subjected to the gradation conversion and the reference image data are compared for each pixel. And a step of performing. In accordance with the type of the mask to be inspected, the method further includes the step of setting the light quantity for inspection, the imaging time of the sensor, the sensor gain, and the gradation conversion table for gradation conversion according to a predetermined recipe. ,
In the plurality of gradation conversion tables, a change degree for gradation conversion according to a gradation value or a gradation region is variably created,
When comparing, a plurality of threshold values are selectively used according to the gradation value or the gradation region,
The reference image data is gradation-converted at the same gradation conversion table ratio as the optical image data,
Based on the gradation level indicated by the reference data, for each pixel, it is determined whether the gradation value of the reference data is a gradation area where the gradation resolution is increased or a gradation area where the gradation resolution is reduced in the optical image data. Is done.

  In addition, according to the embodiment, the pattern inspection method includes a light amount for inspection, a sensor imaging time, a sensor gain setting, and a gradation according to a predetermined recipe according to the type of mask to be inspected. The method includes a step of setting a gradation conversion table for conversion, and a step of performing defect inspection of optical image data captured by the sensor in accordance with the setting.

It is a conceptual diagram which shows the structure of the pattern inspection apparatus in 1st Embodiment. It is a conceptual diagram which shows the flow of the pattern inspection method in 1st Embodiment. It is a figure for demonstrating the acquisition procedure of the optical image in 1st Embodiment. It is a conceptual diagram which shows the internal structure of the sensor output correction circuit in 1st Embodiment. It is a graph which shows an example of the correlation of the gradation conversion table in 1st Embodiment. It is a graph which shows another example of the correlation of the gradation conversion table in 1st Embodiment. It is a graph which shows another example of the correlation of the gradation conversion table in 1st Embodiment. It is a figure which shows an example of the profile of the sensor data before and after the gradation conversion in 1st Embodiment. It is a conceptual diagram which shows the internal structure of the comparison circuit in 1st Embodiment. It is a flowchart which shows an example of the test | inspection recipe in 1st Embodiment. It is a conceptual diagram which shows a response | compatibility when the sensor output level distribution in 1st Embodiment is low. It is a conceptual diagram which shows a response | compatibility when the sensor output level distribution in 1st Embodiment is high. It is a figure which shows an example of the image data and profile of L / S pattern with a low gradation level before the gradation conversion in 1st Embodiment. It is a figure which shows an example of the image data and profile of L / S pattern with a low gradation level after the gradation conversion in 1st Embodiment. It is a conceptual diagram which shows the test | inspection processing flow in the case of performing the die-database test | inspection in 1st Embodiment. It is a conceptual diagram which shows the inspection processing flow in the case of performing the die-die inspection in 1st Embodiment. It is a figure for demonstrating another optical image acquisition method.

(First embodiment)
FIG. 1 is a conceptual diagram showing a configuration of a pattern inspection apparatus according to the first embodiment. In FIG. 1, a pattern inspection apparatus 100 that samples a substrate such as a mask or wafer on which a pattern is formed and inspects defects in the pattern on the sample includes an optical image acquisition unit 150 and a control system circuit 160. . The optical image acquisition unit 150 includes an XYθ table 102, a light source 103, an enlargement optical system 104, a photodiode array 105, a sensor circuit 106, a laser measurement system 122, an autoloader 130, a light quantity sensor 142, and an illumination optical system 170. . In the control system circuit 160, a control computer 110 serving as a computer is connected to a position circuit 107, a comparison circuit 108, a development circuit 111, a reference circuit 112, a sensor output correction circuit 140, and an autoloader control circuit via a bus 120 serving as a data transmission path. 113, a table control circuit 114, a magnetic disk device 109, a magnetic tape device 115, a flexible disk device (FD) 116, a CRT 117, a pattern monitor 118, and a printer 119. The XYθ table 102 is driven by an X-axis motor, a Y-axis motor, and a θ-axis motor. The sensor output correction circuit 140 is an example of a sensor output data correction device. In FIG. 1, description of components other than those necessary for describing the first embodiment is omitted. It goes without saying that the pattern inspection apparatus 100 usually includes other necessary configurations.

  FIG. 2 is a conceptual diagram showing a flow of the pattern inspection method in the first embodiment. FIG. 2 shows, as an example, “die to database (die-to-database) inspection” in which design image data (reference image) is generated and compared with an optical image serving as measurement data obtained by imaging a pattern. .

  As an optical image acquisition step, the optical image acquisition unit 150 acquires an optical image on the photomask 101 that is a sample on which a graphic indicated by graphic data included in the design data is drawn based on the design data. Specifically, the optical image is acquired as follows.

  A photomask 101 to be inspected is placed on an XYθ table 102 provided so as to be movable in a horizontal direction and a rotation direction by motors of XYθ axes, and the pattern formed on the photomask 101 includes an XYθ table. Light is emitted by a suitable light source 103 disposed above 102. The light beam emitted from the light source 103 irradiates the photomask 101 serving as a sample via the illumination optical system 170. A magnifying optical system 104, a photodiode array 105, and a sensor circuit 106 are disposed below the photomask 101, and light that has passed through the photomask 101 that is a sample such as an exposure mask passes through the magnifying optical system 104. Then, an image is formed as an optical image on the photodiode array 105 and is incident thereon. Here, as an example, the case where the photodiode array 105 receives light obtained by illuminating and transmitting the patterned photomask 101 is shown.

FIG. 3 is a diagram for explaining an optical image acquisition procedure according to the first embodiment.
As shown in FIG. 3, the inspection area is virtually divided into a plurality of strip-shaped inspection stripes having a scanning width W in the Y direction, and each of the divided inspection stripes is continuously scanned. Thus, the operation of the XYθ table 102 is controlled, and an optical image is acquired while moving in the X direction. In the photodiode array 105, images having a scan width W as shown in FIG. 2 are continuously input. Then, after acquiring the image of the first inspection stripe, the image of the scan width W is continuously input in the same manner while moving the image of the second inspection stripe in the opposite direction. When an image in the third inspection stripe is acquired, the image moves while moving in the direction opposite to the direction in which the image in the second inspection stripe is acquired, that is, in the direction in which the image in the first inspection stripe is acquired. To get. In this way, it is possible to shorten a useless processing time by continuously acquiring images.

  The pattern image formed on the photodiode array 105 is photoelectrically converted by the photodiode array 105 and further A / D (analog-digital) converted by the sensor circuit 106. In this way, light is converted into an image by photoelectric conversion. The photodiode array 105 is provided with a sensor using a plurality of solid-state imaging elements such as a line sensor, an area sensor, or a TDI (time delay integration) sensor. By continuously moving the XYθ table 102 serving as a stage in the X-axis direction, for example, the TDI sensor images the pattern of the photomask 101 serving as a sample. As described above, the photodiode array 105 as an example of the sensor captures an optical image of the patterned mask to be inspected. These light source 103, magnifying optical system 104, photodiode array 105, and sensor circuit 106 constitute a high-magnification inspection optical system.

  The XYθ table 102 is driven by the table control circuit 114 under the control of the control computer 110. It can be moved by a drive system such as a three-axis (XY-θ) motor that drives in the X, Y, and θ directions.

  The measurement data (optical image) output from the sensor circuit 106 is subjected to light amount correction, offset correction, and gain correction by the sensor output correction circuit 140. Here, in the mask on which the above-described pattern with a reduced signal amplitude is formed, the distribution of the sensor output data (also referred to as gradation value or pixel value) from the captured photodiode array 105 depends on the type of the mask. There is a bias. For example, in an EUV exposure mask, most of sensor output data from the photodiode array 105 is often distributed at a low gradation level. Conversely, there may be a mask in which much of the sensor output data from the photodiode array 105 is distributed at a high gradation level. When the sensor output data distribution level differs depending on the mask type, it may be difficult to obtain sufficient contrast necessary for inspection if only light amount correction, offset correction, and gain correction are performed. There is. Therefore, in the first embodiment, gradation conversion of sensor output data corresponding to the mask type is performed.

FIG. 4 is a conceptual diagram illustrating an internal configuration of the sensor output correction circuit according to the first embodiment. In FIG. 4, the sensor output correction circuit 140 includes a light amount correction circuit 10, a gain correction circuit 20, an offset correction circuit 30, and a gradation conversion circuit 40. The output of the photodiode array 105 A / D converted by the sensor circuit 106 is corrected by the light amount correction circuit 10. As the light amount correction process, the light amount correction circuit 10 outputs, for each pixel, the output of the photodiode array 105 (data after digitization) due to the variation in the inspection light amount based on the measurement value of the inspection light amount data measured by the light amount sensor 142. ) Is corrected. As a gain correction step, the gain correction circuit 12 performs gain correction by inputting a preset gain correction coefficient for each pixel and multiplying the sensor output data by the input gain correction coefficient. As an offset correction step, the offset correction circuit 10 inputs a preset offset correction coefficient for each pixel and adds the offset correction coefficient to the sensor output data to offset the sensor output data. That is, the tone value for each pixel of the sensor is corrected to a value obtained by the calculation formula shown by the following formula (1) by gain correction and offset correction.
(1) Fout = Gain × Fin + Offset

  However, Fin indicates a sensor output before correction, Fout indicates a sensor output after correction, and Offset indicates an offset value.

  Next, as a gradation conversion step, the gradation conversion circuit 40 performs gradation conversion on the pixel value of the optical image data captured by the photodiode array 105 along the gradation conversion table using the gradation conversion table. . As described above, the distribution of sensor output data from the captured photodiode array 105 is biased depending on the type of mask. In light intensity correction, offset correction, and gain correction, all gradation values are uniformly converted, so if you try to increase the resolution of some gradation values, the pixel values of other levels of data are clamped to 0 Or a problem such as saturation to the maximum value may occur. Therefore, a plurality of gradation conversion tables created according to the mask types are prepared and stored in a storage device such as the magnetic disk device 109. The gradation conversion circuit 40 selects a gradation conversion table corresponding to the type of the mask to be inspected from the plurality of gradation conversion tables, and the optical imaged by the sensor along the selected gradation conversion table. Tone conversion is performed on pixel values of image data.

  In the example of FIG. 4, a graph showing the correlation between the three gradation conversion tables is shown. In Example 1 of the gradation conversion table, the change ratio of the output gradation with respect to the input gradation is large in the area where the gradation level is low, and the change ratio of the output gradation is increased from the intermediate area to the area where the gradation level of the input data is high. The gradation value is increased while setting it small. As a result, it is possible to increase the gradation resolution in the region where the gradation level of the input data is low. On the contrary, the gradation resolution in the region where the gradation level of the input data is high is kept low. In the second example of the gradation conversion table, the change ratio of the output gradation with respect to the input gradation is small in the area where the gradation level is low, and the change ratio of the output gradation is changed from the intermediate area to the high area of the input data. The gradation value is decreased while setting it large. As a result, the gradation resolution can be lowered from the region where the gradation level of the input data is low to the middle region, and the gradation resolution can be raised in the region where the gradation level of the input data is high. In the example 3 of the gradation conversion table, in the area where the gradation level is low, the change ratio of the output gradation with respect to the input gradation is set large to increase the gradation value, and in the area where the gradation level of the input data is intermediate Regardless of the gradation, the output gradation is set to substantially the same value, and in a region where the gradation level of the input data is high, the change ratio of the output gradation is set large to reduce the gradation value. As a result, the gradation resolution when the gradation level of the input data is in an intermediate region can be made substantially flat, and the gradation resolution can be increased in a region where the gradation level is low and a region where the gradation level is high. As described above, in the plurality of gradation conversion tables, the degree of change for gradation conversion is variably created according to the gradation value or gradation area. As a result, it is possible to increase the resolution of the desired gradation region without saturating the gradation values of other gradation regions to the maximum value or clamping them to the 0 level.

  FIG. 5 is a graph showing an example (four tables) of the gradation conversion table in the first embodiment. All the gradation conversion tables are monotonously increased. FIG. 5 shows an example in which the gradation resolution in a region where the input gradation level is low is raised by a gradation conversion table by linear conversion using a two-stage change rate. The through setting is an example of a gradation conversion table that does not change due to gradation conversion, and there is no change in gradation resolution.

  FIG. 6 is a graph showing another example (four tables) of the gradation conversion table in the first embodiment. All the gradation conversion tables are monotonously increased. FIG. 5 shows an example in which the gradation resolution in the region where the input gradation level is low is raised by a gradation conversion table by non-linear conversion using a change rate that draws a gentle curve.

  FIG. 7 is a graph showing another example of the correlation of the gradation conversion table in the first embodiment. FIG. 5 shows an example in which the gradation resolution in a region where the input gradation level is low is raised by a gradation conversion table using a combination of linear conversion and non-linear conversion using a two-stage change rate that draws a straight line and a gentle curve. ing.

  FIG. 8 is a diagram illustrating an example of a profile of sensor data before and after gradation conversion in the first embodiment. In the sensor data before gradation conversion shown in FIG. 8A, the profile of the region from the 128th to 256th pixel columns is distributed with a high output level, and the gradation amplitude is large and sufficient contrast is obtained. However, the profile of the region from the 256th to 384th pixel columns is distributed with a low output level, the gradation amplitude L is small, and sufficient contrast cannot be obtained. Therefore, as shown in FIG. 8C, the gradation conversion circuit 40 increases the gradation resolution by setting a large change ratio of the output gradation with respect to the input gradation in the region where the gradation level of the input data is low. Then, a gradation conversion table having a two-stage change rate is selected that sets the change ratio of the output gradation with respect to the input gradation to be low by decreasing the gradation resolution from the middle to the high gradation level of the input data. Then, the gradation conversion circuit 40 performs gradation conversion using the selected gradation conversion table. As a result, in the sensor data after gradation conversion shown in FIG. 8B, the profile of the region from the 256th to 384th pixel columns is about four times larger from the gradation amplitude L to the gradation amplitude L ′. Contrast can be obtained. On the other hand, the profile of the region from the 128th pixel to the 256th pixel column has a gradation amplitude reduced to about 60% of the original amplitude, but a sufficient contrast is still obtained. As described above, by performing gradation conversion using the gradation conversion table in which the degree of change for gradation conversion according to the gradation value or gradation area is variably created, the gradation values of other gradation areas are obtained. It is possible to increase the resolution of a desired gradation region without saturating.

  Then, the optical image data (measurement data) whose gradation value is corrected is sent to the comparison circuit 108 together with data indicating the position of the photomask 101 on the XYθ table 102 outputted from the position circuit 107. The measurement data is, for example, 8-bit unsigned data, and represents the brightness gradation of each pixel.

  In addition, as a reference data creation step, reference data for comparison with measurement data based on design data of a photomask 101 that is a reference image creation unit constituted by the development circuit 111, the reference circuit 112, and the like to be inspected. Reference image). The design data is stored in the magnetic disk device 109 or the like. Here, since the measurement data is subjected to gradation conversion as described above, the reference data is also subjected to gradation conversion in the reference circuit 112 at the same gradation conversion table ratio. Thereby, the gradation levels of the measurement data and the reference data can be matched.

  As a comparison process, the comparison circuit 108 (comparison unit) inputs the measurement data and the reference data, and then performs alignment after comparing them. Comparison is made according to a predetermined algorithm, and the presence or absence of a defect is determined for each pixel. The comparison result is output to the pattern monitor 118 or the like.

  Here, in the gradation conversion described above, since the conversion rate varies depending on the gradation region, a uniform determination threshold value cannot be used.

  FIG. 9 is a conceptual diagram showing an internal configuration of the comparison circuit in the first embodiment. The gradation area determination unit 52 indicated by gradation area determination 1 inputs reference data, and the gradation value of the reference data is set to the gradation resolution in the measurement data for each pixel based on the gradation level indicated by the reference data. It is determined whether the gradation region 1 is raised. Similarly, the gradation area determination unit 54 indicated by gradation area determination 2 receives reference data, and the gradation value of the reference data is determined in the measurement data for each pixel based on the gradation level indicated by the reference data. It is determined whether or not the gradation region 2 has a reduced gradation resolution. The determination threshold value selector 56 receives a plurality of determination threshold values 1 and 2 corresponding to the gradation region. Then, based on the result of determining the gradation region from the reference data, the determination threshold selector 56 selects a determination threshold for each pixel. Then, the selected determination threshold value is output to threshold determination circuit 58. On the other hand, the data comparison unit 50 inputs, for each pixel, measurement data and reference data that have undergone gradation conversion. The reference data that has been subjected to gradation conversion is to be compared with the measurement data that has undergone gradation conversion. Then, calculation is performed by a predetermined algorithm using the measurement data and the reference data that are both tone-converted. For example, the difference is calculated. The obtained value is output to the threshold value determination circuit 58. The threshold determination circuit 58 determines whether the value input from the data comparison unit 50 is within the determination threshold for each pixel. As described above, the combination of the data comparison unit 50 and the threshold value determination circuit 58 compares the optical image data and the reference image data for each pixel. And the result is output. As described above, a plurality of determination threshold values are selectively used according to the gradation value or the gradation area, so that the gradation resolution after the conversion by the gradation conversion table is different. , It is possible to set appropriate determination threshold values for defect detection.

  Here, when performing sensor output correction, before inspection, in accordance with a predetermined recipe according to the type of mask to be inspected, for inspection light quantity, sensor imaging time, sensor gain setting, and gradation conversion It is also preferable to set the gradation conversion table.

  FIG. 10 is a flowchart illustrating an example of an inspection recipe according to the first embodiment. First, in S102, it is determined whether or not the output level distribution is low according to the type of mask to be inspected. If the output level distribution is low, the process proceeds to S104, and if not, the process proceeds to S120.

  FIG. 11 is a conceptual diagram showing correspondence when the sensor output level distribution is low in the first embodiment. When the sensor output level distribution is located in a low gradation area, increase the light amount, increase the exposure time (light reception time) of the sensor, increase the sensor gain, or change the gradation of the low gradation level area to the gradation conversion table. Therefore, the resolution of the low gradation region can be increased.

  Therefore, in S104, it is determined whether the light amount can be increased or the sensor exposure time can be increased. If possible, the process proceeds to S106, and if not possible, the process proceeds to S108. When the light amount is increased or the sensor exposure time is increased, the resolution of the low gradation region can be increased. On the other hand, the gradation value of the high gradation region is saturated to the maximum value, and the data is destroyed. For this reason, it is determined that the light amount can be increased or the sensor exposure time can be increased if it is not saturated or if it may be saturated.

  If possible, in S106, the setting of the pattern inspection apparatus 100 is changed so that the light amount increases or the sensor exposure time increases. Alternatively, the setting of the pattern inspection apparatus 100 is changed so that the light amount increases and the sensor exposure time increases.

  Next, in S108, it is determined whether the sensor gain of the photodiode array 105 can be increased. If possible, go to S110, otherwise go to S112. When the sensor gain is increased, the resolution of the low gradation region can be increased, but on the other hand, the gradation value of the high gradation region is saturated to the maximum value, and the data is crushed. Therefore, it is determined that the sensor gain can be increased when the maximum value is not saturated or when it does not matter.

  If possible, in S110, the setting of the pattern inspection apparatus 100 is changed so that the sensor gain of the photodiode array 105 is increased.

  Next, in S112, it is determined whether enlargement by tone conversion of the dark part or gain increase of the gain correction circuit 12 is possible. If possible, the process proceeds to S114, and if not possible, the process proceeds to S130. When the gain of the gain correction circuit 12 is increased, the resolution of the low gradation region can be increased, but on the other hand, the gradation value of the high gradation region is saturated to the maximum value and the data is destroyed. Therefore, it is determined that the gain of the gain correction circuit 12 can be increased when the maximum value is not saturated or when it may be saturated. On the other hand, enlargement by gradation conversion in the dark area uses a gradation conversion table with a different rate of change depending on the gradation area, so that the resolution of the low gradation area does not saturate the maximum gradation value of the high gradation area. Can be high.

  On the other hand, if the output level distribution is not low, in S120, it is determined whether or not a combination of enlargement by gradation conversion of a bright portion or gain increase of the gain correction circuit 12 and offset adjustment of the offset correction circuit 14 is possible. If possible, the process proceeds to S122, and if not possible, the process proceeds to S130.

  FIG. 12 is a conceptual diagram showing correspondence when the sensor output level distribution is high in the first embodiment. When the sensor output level distribution is located in a high gradation region, the gradation of the region with a high gradation level is increased by the gradation conversion table, or the gain of the sensor output correction circuit 140 is increased and the maximum gradation value is saturated. It is possible to increase the resolution of a high gradation region by performing an offset adjustment at a position where it is not performed. The combination of gain increase and offset adjustment can increase the resolution of the high gradation region, but on the other hand, the gradation value of the low gradation region is clamped to 0 and the data is corrupted. Therefore, it is determined that the combination of gain increase and offset adjustment is possible when the data is not destroyed or when the data may be destroyed. On the other hand, enlargement by gradation conversion of bright areas uses a gradation conversion table with a different rate of change depending on the gradation area, so the data of the gradation value of the low gradation area is clamped to 0 and the data is not crushed In particular, the resolution of a high gradation region can be increased.

  After the setting by the recipe before the inspection as described above is completed, the defect inspection of the optical image data picked up by the sensor described above is performed according to the setting.

  FIG. 13 is a diagram illustrating an example of image data and a profile of an L / S pattern with a low gradation level before gradation conversion in the first embodiment. As shown in FIG. 13A, before the gradation conversion, the amplitude of the L / S pattern is low and it is difficult to discriminate the L / S pattern. With such a gradation level, as shown in FIG. 13B, the contrast necessary for the inspection cannot be obtained. On the other hand, the contrast necessary for the inspection is obtained by performing the gradation conversion as shown below.

  FIG. 14 is a diagram illustrating an example of L / S pattern image data and a profile having a low gradation level after gradation conversion in the first embodiment. As shown in FIG. 14A, after gradation conversion, the amplitude of the L / S pattern is low and the L / S pattern can be discriminated. With such a gradation level, as shown in FIG. 14B, a contrast necessary for inspection can be obtained. Before gradation expansion, the gradation level is low and the noise component due to quantization noise is large, and the output level variation that is visible on the image is conspicuous. It can be seen that variations in output level due to noise are improved.

  As described above, in the first embodiment, by correcting the inspection image by gradation conversion, it is possible to expand the gradation level of the inspection pattern of interest and to perform inspection. Further, by expanding the gradation, noise such as quantization noise is improved, the SN of inspection is improved, and sensitivity can be improved.

  Also, according to the inspection recipe, by setting the inspection light quantity, sensor exposure time, sensor gain setting, gradation conversion correction table, output correction circuit gain and offset, the output level of the inspection pattern of interest Therefore, it is possible to improve the SN of the inspection and the inspection sensitivity.

  FIG. 15 is a conceptual diagram showing an inspection process flow when performing a die-database inspection in the first embodiment. As described above, in the die database (DB) inspection, the measurement data is acquired by the sensor, and then gradation conversion is performed. On the other hand, reference data is created from design data (CAD data), and gradation conversion is similarly performed. Then, the measurement data and the reference data, both of which have been subjected to gradation conversion, are compared. However, the example described above is applicable not only to DB inspection but also to die-die (DD) inspection.

  FIG. 16 is a conceptual diagram showing an inspection processing flow when performing die-to-die inspection in the first embodiment. In die-to-die inspection, an optical image is taken from a photomask in which the same pattern is arranged in a stripe region. In such stripe data, since the same pattern is sent and imaged, the sensor data is sequentially subjected to gradation conversion and sent to the comparison circuit 108 and the delay circuit. The delay circuit sends the measurement data after a predetermined time delay to the comparison circuit 108. Thereby, the measurement data of the target die and the measurement data of the comparison target die can be output to the comparison circuit 108 at the same time. As a result, die-to-die inspection can be performed. As described above, the sensor may pick up another optical image data as reference image data from the mask to be inspected, and perform the die-to-die inspection by the comparison circuit 108.

  FIG. 17 is a diagram for explaining another optical image acquisition method. In the configuration of FIG. 1, the photodiode array 105 that simultaneously enters the number of pixels of the scan width W (for example, 2048 pixels) is used. However, the present invention is not limited to this, and as shown in FIG. Each time a constant pitch movement is detected by a laser interferometer while scanning at a constant speed in the direction, a laser scanning optical device (not shown) scans the laser beam in the Y direction, detects transmitted light, A technique of acquiring a two-dimensional image for each size area may be used.

  In the above description, what is described as “˜circuit”, “˜unit”, or “˜process” can be configured by a program operable by a computer. Or you may make it implement by not only the program used as software but the combination of hardware and software. Alternatively, a combination with firmware may be used. When configured by a program, the program is recorded on a recording medium such as a magnetic disk device, a magnetic tape device, an FD, or a ROM (Read Only Memory). For example, the table control circuit 114, the expansion circuit 111, the reference circuit 112, the comparison circuit 108, and each circuit in the sensor output correction circuit 140 that constitute the arithmetic control unit may be configured by electrical circuits. You may implement | achieve as software which can be processed by the computer etc. which are arrange | positioned in the control computer 110 or each circuit. Moreover, you may implement | achieve with the combination of an electrical circuit and software.

  The embodiments have been described above with reference to specific examples. However, the present invention is not limited to these specific examples. For example, in each embodiment, transmitted light is used, but reflected light or transmitted light and reflected light may be used simultaneously. For example, reflected light is used when inspecting an EUV mask.

  Although the reference image is generated from the design data, data of the same pattern captured by a sensor such as a photodiode array may be used. In other words, a die to die inspection or a die to database inspection may be used.

  In addition, although descriptions are omitted for parts and the like that are not directly required for the description of the present invention, such as a device configuration and a control method, a required device configuration and a control method can be appropriately selected and used.

  In addition, all pattern inspection apparatuses, pattern inspection methods, and image alignment methods that include elements of the present invention and that can be appropriately modified by those skilled in the art are included in the scope of the present invention.

DESCRIPTION OF SYMBOLS 10 Light amount correction circuit 20 Gain correction circuit 30 Offset correction circuit 40 Tone conversion circuit 100 Pattern inspection apparatus 101 Photomask 102 XYθ table 103 Light source 104 Magnifying optical system 105 Photodiode array 106 Sensor circuit 108 Comparison circuit 109 Magnetic disk device 140 Sensor output Correction circuit 150 Optical image acquisition unit 160 Control circuit

Claims (2)

A sensor that captures an optical image of a patterned mask to be inspected;
A storage device for storing a plurality of gradation conversion tables created according to the mask type;
An optical image picked up by the sensor along the selected gradation conversion table by selecting a gradation conversion table corresponding to the type of the inspection mask from a plurality of gradation conversion tables stored in the storage device. A gradation conversion unit that converts the pixel value of the image data, and
A comparison unit that inputs reference image data to be compared with optical image data subjected to gradation conversion, and compares the optical image data subjected to gradation conversion with the reference image data for each pixel;
Equipped with a,
In the plurality of gradation conversion tables, a change degree for gradation conversion according to a gradation value or a gradation region is variably created,
The comparison unit selectively uses a plurality of thresholds according to the gradation value or the gradation region when comparing,
The reference image data is gradation-converted at the same gradation conversion table ratio as the optical image data,
Based on the gradation level indicated by the reference data, for each pixel, it is determined whether the gradation value of the reference data is a gradation area where the gradation resolution is increased or a gradation area where the gradation resolution is reduced in the optical image data. pattern inspection apparatus characterized by being. A step in which a sensor captures an optical image of the patterned mask to be inspected;
Select and select a gradation conversion table corresponding to the type of the mask to be inspected from a plurality of gradation conversion tables stored in a storage device that stores a plurality of gradation conversion tables created according to the mask type A step of gradation-converting the pixel value of the optical image data captured by the sensor along the gradation conversion table,
Inputting reference image data to be compared with gradation-converted optical image data, and comparing the gradation-converted optical image data with the reference image data for each pixel;
Equipped with a,
In accordance with the type of the mask to be inspected, the method further includes the step of setting the light quantity for inspection, the imaging time of the sensor, the sensor gain, and the gradation conversion table for gradation conversion according to a predetermined recipe. ,
In the plurality of gradation conversion tables, a change degree for gradation conversion according to a gradation value or a gradation region is variably created,
When comparing, a plurality of threshold values are selectively used according to the gradation value or the gradation region,
The reference image data is gradation-converted at the same gradation conversion table ratio as the optical image data,
Based on the gradation level indicated by the reference data, for each pixel, it is determined whether the gradation value of the reference data is a gradation area where the gradation resolution is increased or a gradation area where the gradation resolution is reduced in the optical image data. pattern inspection method characterized in that it is.