Pattern inspection device and method for inspecting pattern

Abstract

PURPOSE: To provide an inspection device which can reduce the processing time before a filter function suitable for an inspection of this time can be obtained.CONSTITUTION: A pattern inspection device 100 includes: an optical image acquisition mechanism 150 for acquiring an optical image of an inspection target sample formed by patterning; a parameter range setting unit 62 for setting the range of a reference image generation parameter according to the accordance with a previous inspection condition parameter; a filter function generation unit 64 for generating a plurality of filter functions by using values in the set range of the reference image generation parameter; a determination unit 84 for determining candidates of filter functions for creating a reference image among the generated candidates of the filter functions; a reference circuit 112 for creating a reference image by using the determined filter function; and a comparison circuit 108 for comparing the optical image and the reference image.SELECTED DRAWING: Figure 3

Description

[Technical field]

[0001] One aspect of the present invention relates to a pattern inspection apparatus and a pattern inspection method, for example, to a pattern inspection technique for inspecting a pattern defect of an object serving as a sample used in semiconductor manufacturing, and to a method for inspecting a defect of a mask used when manufacturing a semiconductor element. [Background technology]

[0002] In recent years, with the increasing integration and capacity of large scale integrated circuits (LSI), the circuit line width required for semiconductor elements has become increasingly narrow. These semiconductor elements are manufactured by forming circuits by exposing and transferring a pattern onto a wafer using a reduced projection exposure device called a stepper, using an original pattern (also called a mask or reticle, hereafter collectively referred to as a mask) on which a circuit pattern is formed.

[0003] Improving yield is essential for the manufacture of LSIs, which are very costly to manufacture. However, as typified by 1-gigabit-class DRAMs (random access memories), the patterns that compose LSIs are approaching the submicron to nanometer order. One of the major factors that reduce yield is pattern defects in the masks used when exposing and transferring ultra-fine patterns onto semiconductor wafers using photolithography technology. In recent years, as the dimensions of LSI patterns formed on semiconductor wafers become finer, the dimensions that must be detected as pattern defects have also become extremely small. For this reason, there is a need for high-precision pattern inspection equipment that inspects defects in transfer masks used in LSI manufacturing.

[0004] A known inspection method is to compare an optical image of a pattern formed on a sample such as a lithography mask captured at a predetermined magnification using a magnifying optical system with design data. For example, there is a "die to database inspection" in which the pattern design CAD data is converted into a device input format for input by a drawing device when drawing the pattern on the mask, and the drawing data (design pattern data) is input to an inspection device, a design image (reference image) is generated based on the CAD data, and the design image is compared with an optical image of the pattern as measurement data. In the inspection method using such an inspection device, the sample is placed on a stage, and the stage is moved so that a light beam scans the sample, and the inspection is performed. The light beam is irradiated onto the sample by a light source and an illumination optical system. The light transmitted through or reflected from the sample is imaged on a sensor via the optical system. The image captured by the sensor is sent to a comparison circuit as measurement data. In the comparison circuit, after aligning the images, the measurement data and the reference data are compared according to an appropriate algorithm, and if they do not match, it is determined that there is a pattern defect.

[0005] The pixel data of the optical image captured from the sample is in a filtered state due to the resolution characteristics of the optical system used for capturing the image, in other words, in a continuously changing analog state, so the image intensity (grayscale value) differs from the design image, which is a digital value. Therefore, a filter process is applied to the design image to create a reference image that is close to the measurement image, and then a comparison process is performed.

[0006] In recent years, there has been a demand for improved inspection accuracy in line with the trend toward finer patterns, and in order to improve inspection accuracy, it is necessary to improve the accuracy of such filter processing. For this purpose, many filter functions are generated using a wide range of reference image generation parameters. Then, a filter function that can approximate the measurement image is selected from the many filter functions. Generating such many filter functions requires a huge amount of processing, and it takes a long time to obtain the optimal filter function.

[0007] Here, for an inspection with similar inspection conditions to those of a past inspection, many filter functions are generated in the same way, which results in a huge amount of processing, and it takes a long time to obtain an optimal filter function, which results in a long time before the actual inspection can start. Therefore, when the inspection conditions are the same as or similar to those of a past inspection, it has been considered to use the filter function used in the past as is for the current inspection (for example, see Patent Document 1).

[0008] However, it has become clear that unless the inspection conditions are completely the same, the desired accuracy may not be obtained even if the filter function used in a similar past inspection is used in the current inspection. On the other hand, if many filter functions are generated as in the past, the processing time will be long, and a long time will be required before the actual inspection can begin. [Prior art documents] [Patent documents]

[0009] [Patent Document 1] JP 2022-182497 A Summary of the Invention [Problem to be solved by the invention]

[0010] Therefore, one aspect of the present invention provides an inspection apparatus and method capable of shortening the processing time required to obtain a filter function suitable for the current inspection. [Means for solving the problem]

[0011] A pattern inspection apparatus according to one aspect of the present invention comprises: an optical image acquisition mechanism for acquiring an optical image of the pattern-formed sample to be inspected; a parameter range setting unit that sets a range of a reference image generation parameter according to a degree of agreement with a past inspection condition parameter; a filter function generating unit that generates a plurality of filter function candidates using values ​​within the set range of the reference image generating parameters; a determination unit that determines a filter function for generating a reference image from among the plurality of generated filter function candidates; a reference image generating unit that generates a reference image by using the determined filter function; a comparison unit for comparing the optical image with a reference image; The present invention is characterized by comprising:

[0012] Also, it is preferable that the reference image generation parameter is at least one of the amount of resizing and the amount of corner rounding.

[0013] In addition, it is preferable that the range of the target reference image generation parameters is set to a range narrower than a preset default range.

[0014] Furthermore, the parameter range setting unit sets a preset default range of the reference image generation parameters when the degree of match is less than a threshold value, The filter function generating unit preferably generates a plurality of filter function candidates for creating the reference image using each one of a plurality of reference image generating parameters within a default range of the reference image generating parameters.

[0015] It is also preferable that the imaging device further comprises a coincidence calculation unit that calculates the coincidence using at least one of a parameter of a pattern condition and a parameter of an imaging condition.

[0016] and a determination unit that uses a plurality of filter function candidates generated within a range of set reference image generation parameters, and determines whether or not there is a reference image candidate whose maximum tone difference is equal to or less than a threshold value, using a maximum tone difference between the reference image and an optical image for each of the plurality of reference image candidates generated by the reference image generation unit, the parameter range setting unit resets a preset default range of the reference image generation parameters when the maximum tone difference exceeds a threshold value in all of the multiple reference image candidates; It is preferable that the filter function generating unit again generates candidates for a plurality of filter functions for creating the reference image by using each one of the plurality of reference image generating parameters within the default range of the reference image generating parameters.

[0017] A pattern inspection method according to one aspect of the present invention includes: acquiring an optical image of the patterned specimen; setting a range of reference image generating parameters according to the degree of agreement with past inspection condition parameters; generating a plurality of filter function candidates using values ​​within the range of the set reference image generation parameters; determining a filter function for generating a reference image from among the plurality of generated filter function candidates; generating a reference image using the determined filter function; comparing the optical image with a reference image and outputting the result; The present invention is characterized by comprising:

[0018] Also, it is preferable that the reference image generation parameter is at least one of the amount of resizing and the amount of corner rounding.

[0019] In addition, it is preferable that the range of the target reference image generation parameters is set to a range narrower than a preset default range. Effect of the Invention

[0020] According to one aspect of the present invention, it is possible to reduce the amount of processing required to obtain a filter function suitable for the current inspection, and therefore the processing time required to obtain a filter function suitable for the current inspection can be shortened. [Brief description of the drawings]

[0021] [Figure 1] FIG. 1 is a configuration diagram showing a configuration of a pattern inspection device according to a first embodiment. [Diagram 2] FIG. 2 is a conceptual diagram for explaining an inspection region in the first embodiment. [Diagram 3] 2 is a block diagram showing an example of the internal configuration of a filter function calculation circuit according to the first embodiment. FIG. [Figure 4] FIG. 2 is a flowchart showing main steps of the pattern inspection method according to the first embodiment. [Diagram 5] FIG. 4 is a diagram showing an example of inspection condition parameters and the weighting of each parameter according to the first embodiment. [Figure 6] 13 illustrates an example of the relationship between the degree of match and the ratio of narrowing the range in the first embodiment. [Figure 7] FIG. 4 is a diagram showing an example of the relationship between reference image generating parameters, filter functions, scores, and rankings in a past examination in the first embodiment. [Figure 8] 6A to 6C are diagrams showing an example of a reference image generation parameter range and a set result in the first embodiment. [Figure 9] FIG. 4 is a diagram showing an example of an internal process of a filter function generating process in the first embodiment. [Figure 10] 4A to 4C are diagrams showing examples of graphic patterns before and after resizing in the first embodiment. [Figure 11] 5A to 5C are diagrams showing examples of figure patterns before and after rounding processing in the first embodiment. [Figure 12] 5 is a diagram for explaining an example of the relationship between a filter function, a design image, and a measurement image in the first embodiment. FIG. [Figure 13] FIG. 4 is a diagram for explaining an example of a method for calculating coefficients of a filter function in the first embodiment. [Figure 14] 4 is a diagram showing an example of an internal configuration of a comparison circuit according to the first embodiment; FIG. [Figure 15] FIG. 13 is a diagram showing an example of a reference image generation parameter range and a set result in a modification of the first embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0022] Embodiment 1 Fig. 1 is a configuration diagram showing the configuration of a pattern inspection apparatus in embodiment 1. In Fig. 1, an inspection apparatus 100 for inspecting a sample, for example, a pattern formed on a mask, includes an optical image acquisition mechanism 150 and a control circuit 160 (control unit).

[0023] The optical image acquisition mechanism 150 includes a light source 103, an illumination optical system 170, a movably arranged XYθ table 102, a magnifying optical system 104, an image sensor 105 (an example of a sensor), a sensor circuit 106, a stripe pattern memory 123, and a laser length measurement system 122. A sample 101 is arranged on the XYθ table 102. The sample 101 includes, for example, a photomask for exposure that transfers a pattern onto a wafer. In addition, a pattern consisting of a plurality of figure patterns to be inspected is formed on this photomask. The sample 101 is arranged on the XYθ table 102 with, for example, the pattern-formed surface facing downward.

[0024] A line sensor or a two-dimensional sensor is used as the imaging sensor 105. For example, a TDI (time delay integration) sensor is preferably used. The TDI sensor has a plurality of photosensor elements arranged two-dimensionally. A predetermined image accumulation time is set for each photosensor element when capturing an image. In the TDI sensor, the output of a plurality of photosensor elements arranged in the scanning direction is integrated and output. The plurality of photosensor elements arranged in the scanning direction capture the same pixel while shifting the time according to the movement of the XYθ table 102. When a line sensor is used, the plurality of photosensor elements are arranged so as to be lined up in a direction perpendicular to the scanning direction.

[0025] 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, an autoloader control circuit 113, a table control circuit 114, a filter function calculation circuit 140, a magnetic disk device 109, a memory 115, a flexible disk device (FD) 116, a CRT 117, a pattern monitor 118, and a printer 119 via a bus 120. The sensor circuit 106 is connected to a stripe pattern memory 123, which is connected to the comparison circuit 108. The XYθ table 102 is driven by an X-axis motor, a Y-axis motor, and a θ-axis motor. The XYθ table 102 is an example of a stage.

[0026] In addition, a series of "circuits" such as the position circuit 107, the comparison circuit 108, the expansion circuit 111, the reference circuit 112, the autoloader control circuit 113, the table control circuit 114, and the filter function calculation circuit 140 have a processing circuit. Such processing circuits include electric circuits, computers, processors, circuit boards, quantum circuits, or semiconductor devices. Each circuit may be configured using the same processing circuit (one processing circuit), or different processing circuits (separate processing circuits). For example, a series of "circuits" such as the position circuit 107, the comparison circuit 108, the expansion circuit 111, the reference circuit 112, the autoloader control circuit 113, the table control circuit 114, and the filter function calculation circuit 140 may be configured and executed by the control computer 110. Input data or calculated results required for the position circuit 107, comparison circuit 108, expansion circuit 111, reference circuit 112, autoloader control circuit 113, table control circuit 114, and filter function calculation circuit 140 are stored in a memory (not shown) in each circuit or memory 115. Input data or calculated results required for the control computer 110 are stored in a memory (not shown) in the control computer 110 or memory 115. The programs for executing the processors etc. may be recorded on recording media such as the magnetic disk device 109, FD 116, or ROM (read only memory).

[0027] In the inspection device 100, a high-magnification inspection optical system is configured by the light source 103, the XYθ table 102, the illumination optical system 170, the magnifying optical system 104, the image sensor 105, and the sensor circuit 106. The XYθ table 102 is driven by a table control circuit 114 under the control of a control computer 110. It can be moved by a driving system such as a three-axis (XY-θ) motor that drives in the X, Y, and θ directions. These X, Y, and θ motors can be, for example, step motors. The XYθ table 102 can be moved in the horizontal and rotational directions by the motors of the X, Y, and θ axes. The moving position of the sample 101 placed on the XYθ table 102 is measured by a laser length measurement system 122 and supplied to a position circuit 107.

[0028] Drawing data (design data) that is the basis for forming a pattern on the sample 101 to be inspected is input from outside the inspection device 100 and stored in the magnetic disk device 109. In the drawing data, a plurality of figure patterns are defined, and each figure pattern is usually composed of a combination of a plurality of element figures. It is also possible for a figure pattern to be composed of a single figure. On the substrate 101 to be inspected, a corresponding pattern is formed based on each of the figure patterns defined in the drawing data.

[0029] 1 illustrates components necessary for explaining the embodiment 1. It goes without saying that the inspection device 100 may include other components that are normally required.

[0030] 2 is a conceptual diagram for explaining the inspection area in the first embodiment. As shown in FIG. 2, the inspection area 10 (whole inspection area) of the sample 101 is virtually divided into a plurality of rectangular inspection stripes 20 having a scan width W of the image sensor 105, for example, in the Y direction. The inspection device 100 then acquires an image (stripe area image) for each inspection stripe 20. For each inspection stripe 20, an image of a figure pattern arranged within the inspection stripe 20 is captured in the longitudinal direction (X direction) of the stripe area using a laser beam (inspection beam). Note that in order to prevent missing an image, it is preferable that the inspection stripes 20 are set so that adjacent inspection stripes 20 overlap with each other by a predetermined margin width.

[0031] The movement of the XYθ table 102 causes the image sensor 105 to move continuously in the X direction relative to the object, thereby acquiring optical images. The image sensor 105 continuously captures optical images of a scan width W as shown in FIG. 2. In the first embodiment, after capturing an optical image of one inspection stripe 20, the image sensor 105 moves in the Y direction to the position of the next inspection stripe 20, and then moves in the reverse direction to similarly capture optical images of the scan width W continuously. That is, imaging is repeated in the forward (FWD)-backward (BWD) directions, which are opposite directions, on the outward and return paths.

[0032] Furthermore, for actual inspection, the stripe region image of each inspection stripe 20 is divided into a plurality of rectangular frame region 30 images (frame images 31) as shown in Fig. 2. Then, inspection is performed for each frame image 31 of the frame region 30. For example, it is divided into a size of 512 x 512 pixels. Therefore, a reference image to be compared with the frame images 31 of the frame region 30 is also created for each frame region 30.

[0033] Here, the imaging direction is not limited to the repetition of forward (FWD)-backward (BWD). Imaging may be performed from one direction. For example, FWD-FWD may be repeated. Or, BWD-BWD may be repeated.

[0034] Here, pixel data of an optical image captured from the sample 101 is in a filtered state due to the resolution characteristics of the optical system used for capturing the image, in other words, in an analog state that changes continuously, and therefore the image intensity (grayscale value) differs from a design image, described later, which has a digital value. Therefore, the design image is filtered to approximate the measured data before comparison processing is performed. In the first embodiment, prior to performing the inspection processing of the sample 101, a filter function for performing such filtering processing is first calculated.

[0035] Fig. 3 is a block diagram showing an example of the internal configuration of the filter function calculation circuit in the embodiment 1. In Fig. 3, the filter function calculation circuit 140 includes storage devices 61, 70, 71, 73, 75 such as magnetic disks, a coincidence calculation section 60, a parameter range setting section 62, a filter function generation section 64, a frame image creation section 72, a tone difference calculation section 80, a judgment section 82, a decision section 84, and an evaluation value calculation section 86. The filter function generation section 64 also includes a resizing section 66, a rounding section 67, and a filter coefficient calculation section 68.

[0036] A series of "units" such as the coincidence calculation unit 60, parameter range setting unit 62, filter function generation unit 64 (resizing unit 66, rounding unit 67, and filter coefficient calculation unit 68), frame image creation unit 72, tone difference calculation unit 80, judgment unit 82, decision unit 84, and evaluation value calculation unit 86 have processing circuits. Such processing circuits include electric circuits, computers, processors, circuit boards, quantum circuits, semiconductor devices, and the like. Furthermore, each "unit" may use a common processing circuit (the same processing circuit), or may use different processing circuits (separate processing circuits). Input data or calculated results required for the coincidence calculation unit 60, parameter range setting unit 62, filter function generation unit 64 (resizing unit 66, rounding unit 67, and filter coefficient calculation unit 68), frame image creation unit 72, tone difference calculation unit 80, judgment unit 82, determination unit 84, and evaluation value calculation unit 86 are stored in a memory (not shown) in the filter function calculation circuit 140 or in memory 115 each time.

[0037] Fig. 4 is a flow chart showing the main steps of the pattern inspection method in the embodiment 1. In Fig. 4, the pattern inspection method in the embodiment 1 performs a series of steps including a coincidence calculation step (S102), a parameter range setting step (S104), a representative frame selection step (S110), a stripe image acquisition step (S114), a representative frame image creation step (S116), a representative design image creation step (S118), a filter function calculation step (S130), a stripe image acquisition step (S202), a frame image creation step (S204), a design image creation step (S212), a reference image creation step (S214), and a comparison step (S230).

[0038] In the coincidence calculation step (S102), the coincidence calculation unit 60 inputs the inspection condition parameters of the current inspection, and calculates the coincidence with the inspection condition parameters of the previous inspection.

[0039] Fig. 5 is a diagram showing an example of inspection condition parameters and the weighting of each parameter in the first embodiment. In Fig. 5, the inspection condition parameters in the first embodiment include, for example, pattern condition parameters and imaging condition parameters. The pattern condition parameters include, for example, mask series name, mask layer name, mask layout name, film type, etc. The imaging condition parameters include, for example, stage speed, inspection sensitivity (S), etc. In the example of Fig. 5, the weighting of the mask series name is 1, the weighting of the mask layer name is 2, the weighting of the mask layout name is 5, the weighting of the film type is 1, the weighting of the stage speed is 1, and the weighting of the inspection sensitivity (threshold) is 2. The weighting values ​​may be set based on experience or the like.

[0040] The parameters of the pattern conditions are defined, for example, as additional information of the drawing data. Alternatively, it is also suitable to obtain them by capturing an ID image (not shown) formed outside the inspection area 10 of the sample 101. The additional information or ID image includes, for example, an identification number of the mask to be the sample 101, a mask series name, a mask layer name, a mask layout name, a film type, and so on. As the mask series name, for example, a name indicating a leading-edge mask, or a name of a mask on which a pattern of a rough pattern size is formed, or other names according to the generation of the mask to be manufactured, are used. As the mask layer name, for example, a name of a layer in the multilayer wiring layer of the semiconductor device is used. As the mask layout name, for example, a name identifying the circuit of the semiconductor device is used. As the film type, for example, a name indicating the type of film used in forming the pattern of the mask to be the sample 101 is used.

[0041] The coincidence calculation unit 60 calculates the coincidence using at least one of the parameters of the pattern conditions and the parameters of the imaging conditions. Here, a case where the calculation is performed using both will be described. The inspection condition parameters of the past inspections are stored in the storage device 61 for each sample that was previously inspected. The coincidence is defined by the following formula (1) using the weights of each parameter of the inspection condition parameters. (1) Degree of agreement = sum of weights of matched parameters / sum of weights of all parameters

[0042] When data on a plurality of samples previously tested are stored in the storage device 61, it is preferable to use the sample with the highest degree of match as the previously tested sample. Alternatively, a preset number or percentage of samples may be selected in descending order of degree of match, starting from the sample with the highest degree of match.

[0043] In the parameter range setting step (S104), the parameter range setting unit 62 changes and sets the range of the target reference image generation parameter according to the degree of agreement with the past inspection condition parameters in order to determine the reference image generation parameters used for reference image generation. At least one of the resizing amount and the corner rounding amount is given as the reference image generation parameters. The range of the target reference image generation parameter is changed from a preset default range. Also, the range of the target reference image generation parameter is set to a range narrower than the preset default range. Specifically, the parameter range setting unit 62 inputs the inspection condition parameters of the inspection, and changes and sets a plurality of values ​​used for reference image generation of at least one of the reference image generation parameters of the resizing amount and the corner rounding amount to a range narrower than the preset default range of the reference image generation parameters according to the degree of agreement with the inspection condition parameters implemented in the past.

[0044] FIG. 6 shows an example of the relationship between the degree of match and the ratio of narrowing the range in the first embodiment. In the example of FIG. 6, when the degree of match is 0 (0%) or more and less than 0.2 (20%), 100% of the default reference image generation parameter range is used. When the degree of match is 0.2 (20%) or more and less than 0.4 (40%), 80% of the default reference image generation parameter range is used. When the degree of match is 0.4 (80%) or more and less than 0.6 (60%), 60% of the default reference image generation parameter range is used. When the degree of match is 0.6 (80%) or more and less than 0.8 (80%), 40% of the default reference image generation parameter range is used. When the degree of match is 0.8 (80%) or more and less than 1 (100%), 20% of the default reference image generation parameter range is used. When the degree of match is 1 (100%), 20% of the default reference image generation parameter range may be used, or the past reference image generation parameters that matched may be used as they are. Alternatively, a preset ratio within 0 to 20% of the default reference image generation parameter range may be used.

[0045] Alternatively, a threshold value Tth may be set in advance for the degree of matching, and the parameter range setting unit 62 may set a default range for the reference image generation parameters when the calculated degree of matching is less than the threshold value Tth. In other words, when the degree of matching is less than the threshold value Tth, it is preferable to use 100% of the default range of reference image generation parameters. The example in Fig. 6 shows that, for example, when the degree of matching is less than 0.6, 100% of the default range of reference image generation parameters is used.

[0046] The contents of the ratios used within the default reference image generation parameter range are set as follows:

[0047] FIG. 7 is a diagram showing an example of the relationship between the reference image generating parameters, the filter function, the score, and the rank in the past inspection in the first embodiment. In the example of FIG. 7, the reference image generating parameters include a resize amount and a rounding amount. In the example of FIG. 7, a case where a range of A1 to An is set as the default resize amount range. Also, a case where a range of B1 to Bm is set as the default rounding amount range. Such a range may be determined by empirical rules or the like. When determining the filter function for generating the reference image, a plurality of resize amounts A1, A2, A3, . . . , An at preset intervals within the resize amount range are used. Similarly, a plurality of rounding amounts B1, B2, B3, . . . , Bm at preset intervals within the rounding amount range are used. Then, filter functions a1, a2, a3,... are generated for all combinations of multiple resizing amounts A1, A2, A3,..., An and multiple rounding amounts B1, B2, B3,..., Bm. At this time, for each combination, an evaluation value of the generated filter function is calculated as a score value. As the evaluation value, for example, it is preferable to use the sum of squares of the gradation difference for each pixel between a reference image created using the generated filter function and a corresponding measured image (optical image), or the square root of the sum of squares of the difference. Alternatively, it is preferable to use the maximum gradation difference for each pixel between a reference image created using the generated filter function and a corresponding measured image (optical image). The example of FIG. 7 shows a case where the square root of the sum of squares of the difference is used. Then, for each combination, the ranking is recorded in ascending order of score. A list of the relationships between the reference image generating parameters, filter functions, scores, and rankings is created for each past inspection, and is stored in the storage device 61 as past data in association with the sample to be inspected.

[0048] In past inspections, it was necessary to select and determine the optimal filter function from among all these combinations of filter functions within the default range each time. In this way, a preset default reference image generation parameter range is used for samples inspected in the past. Therefore, it was necessary to generate many combinations of filter functions, and a lot of processing and time were required for the calculation to generate the filter function for generating the reference image. Therefore, in the first embodiment, instead of generating filter functions for all these combinations, the range of the reference image generation parameters or the number of values ​​to be used is changed or narrowed down. Specifically, the range of parameter values ​​to be used for at least one of the default range of the resizing amount and the default range of the rounding amount is changed. Specifically, it operates as follows.

[0049] The parameter range setting unit 62 sets combinations in proportions according to the degree of matching from the top ranking combinations based on the data of past inspections. For example, if the degree of matching is 0.9, combinations of resizing and rounding amounts within a range narrowed down to the top 20% are extracted, and the extracted combinations of resizing and rounding amounts are set.

[0050] FIG. 8 is a diagram showing an example of a reference image generation parameter range and a set result in the first embodiment. In the example of FIG. 8, the vertical axis indicates the rounding amount, and the horizontal axis indicates the resizing amount. In the range of A1 to An, which is the default resizing amount range, there are n resizing amount values. In the range of B1 to Bm, which is the default rounding amount range, there are m rounding amount values. The default range may be set according to an empirical rule. Therefore, there are (m×n) combinations of resizing amount and rounding amount. In the first embodiment, of these (m×n) combinations, N% combinations according to the degree of matching are extracted in order from the smallest score, so that the number of combinations used to generate a filter function can be narrowed down below the number of combinations in the default range. In the example of FIG. 8, an example of a plurality of narrowed down combinations is shown.

[0051] In the representative frame selection step (S110), a representative frame used to obtain a filter function is selected when inspecting the sample 101. The stripe region of each inspection stripe 20 is divided into, for example, a plurality of frame regions 30 as shown in FIG. 2, and inspection is performed for each frame region 30. In other words, the inspection region 10 of the sample 101 is virtually divided into a plurality of frame regions 30, and inspection is performed for each frame region 30. Here, a frame region (representative frame 32) used to generate a filter function is selected from the inspection region 10 of the sample 101. The position of the frame region (representative frame 32) to be selected may be arbitrarily set in advance by the user. Then, the position of the selected frame region may be set in the control computer 110. Alternatively, a predetermined selection condition may be set, and the control computer 110 may select the position of the frame region.

[0052] In the stripe image acquiring step (S114), the optical image acquiring mechanism 150 acquires an optical image of the inspection stripe 20 including the representative frame 32 of the photomask that is the sample 101. More specifically, the operation is as follows.

[0053] First, the XYθ table 102 is moved to a position where the inspection stripe 20 including the representative frame 32 can be imaged. A laser light having a wavelength of less than ultraviolet (e.g., DUV light) serving as inspection light is irradiated onto the pattern formed on the sample 101 from an appropriate light source 103 via an illumination optical system 170. The light transmitted through the sample 101 passes through a magnifying optical system 104 and is focused as an optical image on an imaging sensor 105 (an example of a sensor), and is incident thereon.

[0054] The pattern image formed on the image sensor 105 is photoelectrically converted by each light receiving element of the image sensor 105, and further A / D (analog-digital) converted by the sensor circuit 106. Then, pixel data of the inspection stripe 20 to be measured is stored in the stripe pattern memory 123. Thereafter, the stripe area image is sent to the filter function calculation circuit 140 together with data indicating the position of the sample 101 on the XYθ table 102 output from the position circuit 107. The measurement data (pixel data) is, for example, 8-bit unsigned data, and represents the brightness gradation (light amount) of each pixel. The stripe area image output to the filter function calculation circuit 140 is stored in the storage device 71.

[0055] In the representative frame image creating step (S116), the frame image creating unit 72 creates a frame image (representative frame image) of the representative frame 32. Specifically, the stripe region image is divided in the x direction at a predetermined size so as to cut out the frame image (representative frame image) of the representative frame 32 from the stripe region image (optical image) of the inspection stripe 20 including the representative frame 32. For example, the stripe region image is divided into frame images of 512×512 pixels. Data of the divided representative frame images is output to the storage device 73 and stored therein.

[0056] In the representative design image creation step (S118), the development circuit 111 (an example of a design image creation unit) creates a design image (representative design image) by image development based on the design pattern data that is the basis for pattern formation of the inspected sample 101. Specifically, the design data is read from the magnetic disk device 109 through the control computer 110, and each figure pattern in the area of ​​the representative frame 32 defined in the read design data is converted into binary or multi-value image data (image development) to create the design image (representative design image).

[0057] Here, the figures defined in the design pattern data are, for example, rectangles and triangles as basic figures, and graphic data (vector data) is stored that defines the shape, size, position, etc. of each pattern figure using information such as the coordinates (x, y) at the reference position of the figure, the length of the sides, and a graphic code that serves as an identifier to distinguish the type of figure, such as a rectangle or triangle.

[0058] When the design pattern information that constitutes such graphic data is input to the expansion circuit 111, it is expanded into data for each graphic, and the graphic code indicating the graphic shape of the graphic data, the graphic dimensions, etc. are interpreted. Then, binary or multi-value design image data is expanded as a pattern to be placed within a grid having a grid unit of a predetermined quantized dimension, and output. In other words, the design data is read, the inspection area is virtually divided into grids having a predetermined dimension unit, and the occupancy rate of the graphic in the design pattern is calculated for each grid, and n-bit occupancy data is output. For example, it is preferable to set one grid as one pixel. Then, 1 / 2 pixel is assigned to one pixel. 8 If a resolution of (=1 / 256) is to be given to the pixel, a small area of ​​1 / 256 is allocated for the area of ​​the figure placed in the pixel to calculate the occupancy rate within the pixel. Then, a design image of 8-bit occupancy data is created for each pixel. The data of the design image is output to the filter function calculation circuit 140 and stored in the storage device 70.

[0059] In the filter function calculation step (S130), the filter function calculation circuit 140 calculates a filter function for generating a reference image. Specifically, the operation is as follows.

[0060] Fig. 9 is a diagram showing an example of internal steps of the filter function generating step in the embodiment 1. In Fig. 9, the filter function computing step (S130) performs, as its internal steps, a series of steps including a filter function generating step (S131), a tone difference calculating step (S138), a judgment step (S140), a default setting step (S142), an evaluation value calculating step (S144), and a filter function determining step (S146). The temporary filter function generating step (S131) ​​performs, as its internal steps, a resizing step (S132), a rounding step (S134), and a filter coefficient calculating step (S136).

[0061] In the filter function generating step (S131), the filter function generating unit 64 generates a filter function for creating a reference image using a value within the range of the set reference image generating parameters. Specifically, the filter function generating unit 64 generates a plurality of filter function candidates for creating a reference image using each of a plurality of values ​​within the changed or narrowed down range of the reference image generating parameters. Specifically, the filter function candidates are generated for each of the narrowed down combinations of resize amount and rounding amount. A more detailed explanation will be given below.

[0062] First, in a resizing step (S132), the resizing processor 66 resizes the graphic pattern in the design image of the representative frame 32 by using one of a plurality of values ​​within the range of the changed or narrowed-down reference image generating parameters. Specifically, the graphic pattern in the design image of the representative frame 32 is resized for each of the narrowed-down combinations of the resizing amount and the rounding amount.

[0063] FIG. 10 is a diagram showing an example of a figure pattern before and after resizing in the first embodiment. The example of FIG. 10 shows a figure pattern 14 in which the width size of the figure pattern 12 in the design image is resized by a resize amount A'. If the default range of the resize amount is, for example, from -5 pixels to +5 pixels, it is assumed that the resize amount is changed and set or narrowed down to, for example, seven values ​​of 0.5 pixels each in the range of -1 pixel to +2 pixels (-1 pixel, -0.5 pixel, 0, +0.5 pixel, +1 pixel, +1.5 pixel, +2 pixels). A negative value indicates that the width size is resized in a direction that reduces the width size. A positive value indicates that the width size is resized in a direction that increases the width size. For example, 0.5 pixel indicates that the resize amount is 1 / 2 the pixel size. The example of FIG. 10 shows a case where the width size of the figure pattern 12 is resized in a direction that reduces the width size. In the example of FIG. 10, an example of resizing the width size in the x direction is shown, but the width size in the y direction may be resized instead of the width size in the x direction. Alternatively, both the width size in the x direction and the width size in the y direction may be resized.

[0064] Next, in a rounding process step (S134), the rounding processor 67 rounds corners of the graphic pattern in the design image of the representative frame 32 using one of a plurality of values ​​within the range of the changed or narrowed-down reference image generation parameters. Specifically, for each of the plurality of narrowed-down combinations of resize amount and rounding amount, the rounding processor 67 rounds corners of the graphic pattern in the design image of the representative frame 32. It is preferable to perform the rounding process on the graphic pattern after resizing.

[0065] FIG. 11 is a diagram showing an example of a graphic pattern before and after rounding in the first embodiment. In the example of FIG. 11, a graphic pattern 16 is shown in which the corners of a resized graphic pattern 14 are rounded by a rounding amount B'. If the default range of the rounding amount is, for example, from 0 to +2 pixels, it is changed or narrowed down to, for example, five values ​​(0.2 pixels, 0.4 pixels, 0.6 pixels, 0.8 pixels, 1 pixel) of 0.2 pixels each in the range from 0.2 pixels to 1 pixel. Also, for example, 0.2 pixels indicates a rounding amount of 1 / 5 the pixel size. The rounding amount indicates a radius of curvature. In the example of FIG. 11, the upper left corner is shown, but other corners are similarly rounded.

[0066] In the filter coefficient calculation step (S136), the filter coefficient calculation unit 68 calculates the coefficient of a filter function using a design image that has been resized and / or rounded using each of a plurality of values ​​within the range of the changed or narrowed-down reference image generation parameters. Specifically, the filter function coefficient is calculated using a design image that has been resized and / or rounded for each of the plurality of narrowed-down combinations of resize amounts and round amounts.

[0067] FIG. 12 is a diagram for explaining an example of the relationship between the filter function, the design image, and the measurement image in the first embodiment. In FIG. FIG. 13 is a diagram for explaining an example of a method for calculating coefficients of a filter function in the first embodiment. For example, as shown in FIG. 12, an unknown coefficient matrix a(i,j) (an example of a filter function) consisting of k×k elements, which is less than the number of pixels in the frame region, is obtained by the following method. For example, a 15×15 coefficient matrix a(i,j) is obtained for an image of a frame region consisting of 512×512 pixels. The sum of the products of the pixels of k×k pixels and the coefficient matrix a(i,j) is divided by the number of pixels N (=k×k) with a pixel of interest d(i,i) of the representative design image that has been resized and / or rounded as the center to obtain a coefficient matrix a(i,j) that is closer to the pixel of interest r(i,i) of the representative frame image corresponding to the pixel of interest d(i,i). Such a relational expression (2) is shown below.

[0068]

number

[0069] As shown in FIG. 13, while the pixel of interest is moved within the representative frame 32, the relational expression (2) is calculated each time. Then, the coefficient matrix a(i,j) that best satisfies the relational expression (2) defined using the unknown coefficient matrix a(i,j) obtained for each of all pixels within the representative frame 32 is obtained. The number of elements k×k of the coefficient matrix a(i,j) may be set appropriately. If the number is too small, the accuracy will deteriorate, and if the number is too large, the calculation time will be long. Also, when the pixel of interest moves within the representative frame 32, if it is close to an end, there may not be enough surrounding pixels on the end side. In such a case, the calculation may be performed using the surrounding pixels and the number of pixels N from which values ​​can be obtained.

[0070] As a result of the above, the coefficient matrix a(i,j) of the filter function for each of the multiple combinations of the resizing amount and the rounding amount that have been narrowed down is obtained. These multiple coefficient matrices a(i,j) are candidates for the filter function to create the reference image. It is necessary to select the true filter function from these multiple coefficient matrices a(i,j).

[0071] If the degree of match is less than the threshold value Tth, the parameter range setting unit 62 may set a preset default range of the reference image generation parameters. In this case, the filter function generating unit 64 generates a plurality of filter function candidates for creating a reference image using each of a plurality of reference image generation parameters within the default range of the reference image generation parameters. In this way, if the degree of match is low, the use range of the reference image generation parameters may not be narrowed down.

[0072] In the tone difference calculation step (S138), first, the reference circuit 112 creates a plurality of reference image candidates using a plurality of filter function candidates generated within the range of the reference image generation parameters that have been changed or narrowed down. Specifically, the operation is as follows. For each of the plurality of combinations of the narrowed down combinations of the resize amount and the rounding amount, the reference circuit 112 creates a reference image candidate corresponding to the representative frame image using the filter function candidate for the combination. The reference circuit 112 first performs resizing and rounding processing for the combination on the pattern in the design image of the representative frame area 32, and then creates reference image data for each pixel of the design image by dividing the sum of the products of the pixels of k×k pixels and the coefficient matrix a(i,j) that is the filter function for the combination, with the pixel d(i,i) at the center, by the number of pixels N (=k×k). The obtained reference image data is sent to the filter function calculation circuit 140 and stored in the storage device 75.

[0073] Next, the gradation difference calculation unit 80 calculates the gradation difference Δ by subtracting the pixel value of the measurement image from the pixel value of the reference image for each of the multiple combinations of the resizing amount and the rounding amount that have been narrowed down. Such a gradation difference is calculated for each pixel in the image.

[0074] In the determination step (S140), the determination unit 82 determines whether or not there is a candidate reference image whose maximum grayscale difference Δmax is equal to or smaller than a threshold value ΔTh, using the maximum grayscale difference Δmax between each of the multiple candidate reference images and the representative frame image (optical image). The maximum grayscale difference Δmax indicates the maximum value of the multiple grayscale differences Δ obtained for all pixels in the image.

[0075] If there is no reference image candidate whose maximum tone difference Δmax is equal to or less than the threshold value ΔTh among the multiple reference image candidates, the process proceeds to a default setting step (S142).If there is a reference image candidate whose maximum tone difference Δmax is equal to or less than the threshold value ΔTh, the process proceeds to an evaluation value calculation step (S144).

[0076] In the default setting step (S142), the parameter range setting unit 62 resets the default range of the reference image generation parameters when the maximum tone difference Δmax exceeds the threshold value ΔTh for all of the multiple reference image candidates. In other words, the range is too narrow for the multiple combinations of resizing amount and rounding amount that have been narrowed down, so the default range is set again. Then, returning to the filter function generation step (S131), the filter function generation unit 64 again generates multiple filter function candidates for creating a reference image using each of the multiple reference image generation parameters within the default range of the reference image generation parameters. Then, the tone difference calculation step (S138) and the determination step (S140) are performed.

[0077] In the evaluation value calculation step (S144), the evaluation value calculation unit 86 calculates an evaluation value of a filter function that has created a reference image candidate in which the maximum gradation difference Δmax is equal to or smaller than a threshold value ΔTh. As the evaluation value, it is preferable to use the already calculated gradation difference Δ, for example, the sum of squares of the gradation difference in the image (sum of squared differences) or the square root of the sum of squared differences. When the maximum gradation difference is used as the evaluation value, this step is omitted since it has already been calculated. The calculated evaluation value is recorded as the score value described above, together with the reference image generation parameters and the filter function. It will be used as one of the past data when inspecting future samples.

[0078] In the filter function determination step (S146), the determination unit 84 determines a true filter function for creating a reference image from among the multiple filter function candidates generated. For example, if there is one reference image candidate whose maximum gradation difference Δmax is equal to or less than the threshold value ΔTh, the filter function used to create the reference image is determined as the true filter function. For example, if there are two or more reference image candidates whose maximum gradation difference Δmax is equal to or less than the threshold value ΔTh, it is preferable to determine the filter function used to create the reference image whose evaluation value (e.g., the square root of the sum of squared differences) obtained in the evaluation value calculation step (S144) is smaller (the one with the higher score ranking) as the true filter function.

[0079] As described above, by changing or narrowing the range of the reference image generation parameters according to the degree of coincidence, the amount of processing required for generating the filter function can be reduced and the time can be shortened. The determined filter function (coefficient matrix) is set in the reference circuit. Similarly, the resizing amount and rounding amount at that time are also set in the reference circuit. Then, the inspection process of the entire sample 101 is started.

[0080] FIG. 14 is a diagram showing an example of the internal configuration of the comparison circuit in the first embodiment. In FIG. 14, the comparison circuit 108 includes storage devices 50, 52, 56 such as magnetic disk devices, a frame image creation unit 54, a positioning unit 57, and a comparison unit 58. A series of "units" such as the frame image creation unit 54, the positioning unit 57, and the comparison unit 58 have processing circuits. Such processing circuits include electric circuits, computers, processors, circuit boards, quantum circuits, or semiconductor devices. In addition, each "unit" may use a common processing circuit (the same processing circuit). Alternatively, different processing circuits (separate processing circuits) may be used. Input data or calculation results required for the frame image creation unit 54, the positioning unit 57, and the comparison unit 58 are stored in a memory (not shown) in the comparison circuit 108 or in the memory 115 each time.

[0081] In a stripe image acquiring step (S202) (also called a scanning step or an optical image acquiring step), the optical image acquiring mechanism 150 acquires an optical image of the photomask serving as the sample 101. The method of acquiring the stripe image is the same as that described above. However, in this case, the stripe images are acquired in order as shown in FIG. 2. Then, pixel data is stored in the stripe pattern memory 123 for each inspection stripe 20. Thereafter, the stripe area image is sent to the comparison circuit 108 together with data indicating the position of the photomask 101 on the XYθ table 102 output from the position circuit 107. The measurement data (pixel data) is, for example, 8-bit unsigned data, and expresses the brightness gradation (light amount) of each pixel. The stripe area image output to the comparison circuit 108 is stored in the storage device 50.

[0082] As a frame image creating step (S204), in the comparison circuit 108, the frame image creating section 54 generates a plurality of frame images 31 by dividing the stripe region image (optical image) at a predetermined width. Specifically, as shown in FIG. 2, the stripe region image is divided into frame images of a plurality of rectangular frame regions 30. For example, the image is divided into frames of 512×512 pixels. Data of each frame region 30 is stored in the storage device 56.

[0083] In the design image creation step (S212), the development circuit 111 (design image creation unit) develops an image based on the design pattern data that is the basis for pattern formation of the inspected sample 101 to create a design image. Specifically, the development circuit 111 reads out the design data from the magnetic disk device 109 through the control computer 110, and converts each figure pattern of each frame area 30 defined in the read out design data into binary or multi-value image data. Then, a design image of 8-bit occupancy data for each pixel is created. The design image data (image data) is output to the reference circuit 112.

[0084] In the reference image creation step (S214), the reference circuit 112 (reference image creation unit) creates a reference image to be compared with the optical image, using the determined true filter function. Specifically, the reference circuit 112 resizes and rounds the design image according to the set resizing amount and rounding amount, and then performs filtering using the set coefficient matrix a(i,j) (one example of a filter function) to create a reference image. The created reference image is output to the comparison circuit 108, and the reference image output in the comparison circuit 108 is stored in the storage device 52. In this way, the other image (reference image) data to be compared for inspection is generated.

[0085] The coefficient matrix a(i,j) (an example of a filter function) calculated using the representative design image of the representative frame is used for filtering all design images (plural design images) having different frame regions 30 in the inspection region 10. In other words, the plural design images are each filtered using the same calculated filter function.

[0086] In the comparison step (S230), the comparison circuit 108 (an example of a comparison unit) compares the captured optical pixels with the reference image and outputs the result. Specifically, it operates as follows. First, the alignment unit 57 reads out the frame image (optical image) to be compared from the storage device 56, and similarly reads out the reference image to be compared from the storage device 52. Then, alignment is performed using a predetermined algorithm. For example, alignment is performed using the least squares method. Then, the comparison unit 58 compares the two for each pixel according to a predetermined judgment condition, and judges the presence or absence of a defect such as a shape defect. As the judgment condition, for example, the two are compared for each pixel according to a predetermined algorithm, and judges the presence or absence of a defect. Then, the comparison result is output. The comparison result may be output to, for example, the magnetic disk device 109, the flexible disk device (FD) 116, the CRT 117, the pattern monitor 118, or the printer 119.

[0087] FIG. 15 is a diagram showing an example of a reference image generation parameter range and a set result in a modification of the first embodiment. In the example of FIG. 15, the vertical axis indicates the rounding amount, and the horizontal axis indicates the resizing amount. In the example of FIG. 8, a case is shown in which a plurality of combinations that have been changed or narrowed down to N% according to the degree of matching are used as is, in ascending order of scores, but this is not limited to this. As shown in FIG. 15, it is also preferable to set a circumscribing rectangle of a plurality of combinations that have been changed or narrowed down to N%, and set the combinations within the circumscribing rectangle as the changed or narrowed down parameter combinations. In the example of FIG. 15, the range of resizing amounts is set to Ai to As, and all resizing amounts within a predetermined interval within Ai to As are used. In addition, the range of rounding amounts is set to Bj to Bt, and all rounding amounts within a predetermined interval within Bj to Bt are used.

[0088] As described above, according to the first embodiment, it is possible to reduce the amount of processing required to obtain a filter function suitable for the current inspection, and therefore the processing time required to obtain a filter function suitable for the current inspection.

[0089] The above describes the embodiment with reference to specific examples. However, the present invention is not limited to these specific examples. For example, in the embodiment, a transmitted illumination optical system using transmitted light is shown as the illumination optical system 170, but the present invention is not limited to this. For example, a reflective illumination optical system using reflected light may be used. Alternatively, a transmitted illumination optical system and a reflective illumination optical system may be combined to use transmitted light and reflected light simultaneously.

[0090] The above-mentioned filter functions and filter function coefficients are merely examples, and the present invention is not limited to these. Other filter functions and filter function coefficients may be used.

[0091] In addition, although the description of the device configuration, control method, and other parts that are not directly necessary for the explanation of the present invention are omitted, the required device configuration and control method can be appropriately selected and used. For example, although the description of the control unit configuration that controls the inspection device 100 is omitted, it goes without saying that the required control unit configuration can be appropriately selected and used.

[0092] In addition, all pattern inspection devices and pattern inspection methods that include the 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. [Explanation of symbols]

[0093] 10 Inspection area 20 Inspection Stripes 30 Frame Area 31 Frame Images 32 Representative Frames 54 Frame image creation section 57 Alignment section 58 Comparison section 60 Matching degree calculation part 61,70,71,73,75 Storage device 62 Parameter range setting section 64 Filter function generator 66 Resize processing section 67 Rounding Processor 68 Filter coefficient calculation section 72 Frame image creation section 80 Gradation difference calculation unit 82 Judgment section 84 Decision Section 86 Evaluation value calculation unit 100 Inspection Equipment 101 Sample 102 XYθ table 103 Light source 104 Magnifying Optical System 105 Photodiode Array 106 Sensor Circuit 107 Position circuit 108 Comparison circuit 109 Magnetic disk device 110 Control computer 111 Deployment Circuit 112 Reference circuit 113 Autoloader control circuit 114 Table control circuit 115 Memory 116FD 117 CRT 118 Pattern Monitor 119 Printer 120 Bus 122 Laser length measurement system 123 Stripe Pattern Memory 140 Coefficient calculation circuit 150 Optical image acquisition unit 160 Control Circuits 170 Illumination optical system

Claims

1. an optical image acquisition mechanism for acquiring an optical image of the pattern-formed sample to be inspected; a parameter range setting unit that sets a range of a reference image generation parameter according to a degree of agreement with a past inspection condition parameter; a filter function generating unit that generates a plurality of filter function candidates using values ​​within the set range of the reference image generating parameters; a determination unit that determines a filter function for generating a reference image from among the plurality of generated filter function candidates; a reference image generating unit that generates a reference image by using the determined filter function; a comparison unit that compares the optical image with the reference image; A pattern inspection device comprising:

2. 2. The pattern inspection apparatus according to claim 1, wherein the reference image generation parameter is at least one of a resizing amount and a corner rounding amount.

3. 3. The pattern inspection apparatus according to claim 1, wherein the range of the reference image generation parameters is set to a range narrower than a preset default range.

4. the parameter range setting unit sets a preset default range of the reference image generation parameters when the degree of match is less than a threshold value; 3. The pattern inspection device according to claim 1, wherein the filter function generation unit generates candidates for the plurality of filter functions for creating a reference image using each of a plurality of reference image generation parameters within a default range of the reference image generation parameters.

5. 3. The pattern inspection apparatus according to claim 1, further comprising a coincidence calculation unit that calculates the coincidence using at least one of a parameter of a pattern condition and a parameter of an imaging condition.

6. a determination unit that uses the plurality of filter function candidates generated within the range of the set reference image generation parameters, and determines whether or not there is a reference image candidate whose maximum tone difference is equal to or less than a threshold value, using a maximum tone difference between the reference image and an optical image for each of the plurality of reference image candidates created by the reference image creation unit; the parameter range setting unit resets a preset default range of the reference image generation parameter when the maximum tone difference exceeds a threshold value for all of the plurality of reference image candidates; 3. The pattern inspection device according to claim 1, wherein the filter function generation unit again generates candidates for the plurality of filter functions for creating a reference image using each of a plurality of reference image generation parameters within a default range of the reference image generation parameters.

7. acquiring an optical image of the patterned specimen; setting a range of reference image generating parameters according to the degree of agreement with past inspection condition parameters; generating a plurality of filter function candidates using values ​​within the set range of the reference image generation parameters; determining a filter function for generating a reference image from among the plurality of generated filter function candidates; generating a reference image using the determined filter function; comparing the optical image with the reference image and outputting the result; A pattern inspection method comprising:

8. 8. The pattern inspection method according to claim 7, wherein the reference image generation parameter is at least one of an amount of resizing and an amount of corner rounding.

9. 9. The pattern inspection method according to claim 7, wherein the range of the target reference image generating parameters is set to a range narrower than a preset default range.

Images