JP4448181B2 - Pattern inspection method, pattern inspection apparatus, and program - Google Patents

Description

  The present invention relates to a pattern inspection method, a pattern inspection apparatus, and a program. For example, the present invention relates to a pattern inspection technique for inspecting a pattern defect of an object serving as a sample used in semiconductor manufacturing, when manufacturing a semiconductor element or a liquid crystal display (LCD). The present invention relates to an apparatus for inspecting defects of extremely small patterns such as a photomask, a wafer, or a liquid crystal substrate used, and an inspection method thereof.

  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. For example, drawing is performed using an electron beam or a laser beam.

  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 TFT (Thin Film Transistor) 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, it has become an urgent task to develop a pattern 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 design image data or the same pattern on the sample. It is known to perform an inspection by comparing with a captured optical image. For example, as a pattern inspection method, “die to die inspection” for comparing optical image data obtained by imaging the same pattern at different locations on the same mask, or CAD data used for drawing a mask pattern as an inspection apparatus input format. “Die to database inspection” in which design image data is generated as reference image data based on the converted drawing data (design pattern information), and the reference image data is compared with optical image data as measurement data obtained by imaging the pattern. There is. 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 measured data and the reference data according to an appropriate algorithm after the images are aligned, and determines that there is a pattern defect if they do not match.

  Here, in the die to database inspection (DB inspection), the accuracy of the reference image generation model is important. That is, it is necessary to select the parameters of the reference image generation model so that the reference image and the optical image match as much as possible. Conventionally, some design data and optical images are prepared as learning data, and parameters of a reference image generation model are estimated from these. In estimating parameters, a plurality of estimation results starting from different initial values are obtained, and the best one is selected from the obtained plurality of estimation results.

  However, the parameter estimation performed before the DB check is an optimization for the learning image prepared in advance. Therefore, sufficient parameter optimization is not always performed for patterns that do not appear in the learning image. Therefore, there has been a problem that a pseudo defect may occur due to inconsistency between the reference image and the optical image.

Here, an example of a mechanism for generating a reference image is disclosed in literature (for example, see Patent Literature 1). However, this process does not optimize the parameters sufficiently and does not solve the above-described problem.
JP 2006-268341 A

  As described above, there is a problem in that the accuracy of the reference image generation model is poor and a pseudo defect may occur due to a mismatch between the reference image and the optical image.

  Therefore, an object of the present invention is to provide a pattern inspection method and apparatus capable of overcoming the above-described problems and further improving the accuracy of a reference image generation model.

The pattern inspection method according to one aspect of the present invention includes:
Sample optical image data and design image data defining gradation values corresponding to the sample optical image data are input, and a plurality of coefficients of a predetermined optical model function are obtained using the sample optical image data and the design image data A process of obtaining
Acquiring actual optical image data in the patterned sample to be inspected;
Creating reference image data corresponding to actual optical image data of the sample to be inspected using one of the plurality of coefficients;
Comparing the actual optical image data of the sample to be inspected with the reference image data to detect a defect candidate pattern;
For reference image data including the defect candidate pattern, a step of creating reference image data for the remaining coefficients using the remaining coefficients that are not used for creating the reference image data among the plurality of coefficients,
Comparing each reference image data for the remaining coefficients with actual optical image data including the defect candidate pattern;
Out of a plurality of comparison results between the reference image data for the plurality of coefficients and the actual optical image data including the defect candidate pattern, outputting a comparison result according to a predetermined condition;
It is provided with.

Moreover, the pattern inspection apparatus according to one aspect of the present invention includes:
Sample optical image data and design image data defining gradation values corresponding to the sample optical image data are input, and a plurality of coefficients of a predetermined optical model function are obtained using the sample optical image data and the design image data A coefficient acquisition unit for acquiring
An optical image acquisition unit for acquiring actual optical image data in the patterned sample to be inspected;
A reference image data creating unit that creates reference image data corresponding to actual optical image data of the sample to be inspected, using one of the plurality of coefficients;
A comparison unit that inputs actual optical image data of the sample to be inspected and compares the reference image data;
With
The reference image data creation unit refers to the reference image data including the pattern determined to be defective as a result of the comparison, using the remaining coefficients that are not used for creating the reference image data among the plurality of coefficients. Create image data,
The comparison unit compares the newly created reference image data with actual optical image data including a pattern determined as the defect.

Further, a program for causing a computer of one embodiment of the present invention to execute is as follows.
Sample optical image data and design image data defining gradation values corresponding to the sample optical image data are input, and a plurality of coefficients of a predetermined optical model function are obtained using the sample optical image data and the design image data Acquiring and storing in a storage device;
A process of reading one of the plurality of coefficients from the storage device and using the read coefficient to create reference image data corresponding to actual optical image data of the sample to be inspected;
A process of detecting defect candidate patterns by comparing the actual optical image data acquired from the patterned sample to be inspected and the reference image data;
For the reference image data including the defect candidate pattern, the remaining coefficients that are not used for creating the reference image data among the plurality of coefficients are read from the storage device, and the remaining coefficients are read out using the remaining coefficients that are read. Processing to create reference image data for
A process of comparing each reference image data for the remaining coefficients with actual optical image data including the defect candidate pattern;
Out of a plurality of comparison results between each reference image data for the plurality of coefficients and actual optical image data including the defect candidate pattern, a process of outputting a comparison result according to a predetermined condition;
It is provided with.

  According to the present invention, it is possible to obtain a result of comparison using reference image data created using coefficients of a more appropriate reference image generation model. Therefore, pseudo defects can be reduced. As a result, it is possible to effectively use the apparatus, for example, preventing re-inspection.

Embodiment 1 FIG.
FIG. 1 is a conceptual diagram showing the configuration of the pattern inspection apparatus according to the first embodiment.
In FIG. 1, a pattern inspection apparatus 100 that inspects a defect of a sample using a substrate such as a mask or a wafer includes an optical image acquisition unit 150 and a control 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 length measurement system 122, an autoloader 130, and an illumination optical system 170. In the control circuit 160, a control computer 110 serving as a computer is connected to a position circuit 107, a comparison circuit 108 serving as an example of a comparison unit, an expansion circuit 111, and an example of a reference image data creation unit via a bus 120 serving as a data transmission path. A reference circuit 112, an autoloader control circuit 113, a table control circuit 114, a model coefficient estimation circuit 140, a magnetic disk device 109 as an example of a storage device, a magnetic tape device 115, a flexible disk device (FD) 116, a CRT 117, and a pattern monitor 118. Are connected to the printer 119. The XYθ table 102 is driven by an X-axis motor, a Y-axis motor, and a θ-axis motor. In FIG. 1, constituent parts necessary for explaining the first embodiment are described. It goes without saying that the pattern inspection apparatus 100 may normally include other necessary configurations.

  When performing the inspection, first, before starting the inspection, first, the photomask 101 to be inspected by the autoloader 130 controlled by the autoloader control circuit 113 is moved in the horizontal direction and the rotational direction by the motors of the XYθ axes. It is loaded on an XYθ table 102 that can be provided, and is placed on the XYθ table 102.

  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. For example, step motors can be used as these X motor, Y motor, and θ motor. The movement position of the XYθ table 102 is measured by the laser length measurement system 122 and supplied to the position circuit 107. The photomask 101 on the XYθ table 102 is automatically conveyed from the autoloader 130 driven by the autoloader control circuit 113, and is automatically discharged after the inspection is completed.

FIG. 2 is a diagram for explaining an optical image acquisition procedure according to the first embodiment.
As shown in FIG. 2, the inspection region is virtually divided into a plurality of strip-shaped inspection stripes 20 having a scan width W, for example, in the Y direction. Further, the operation of the XYθ table 102 is controlled so that the divided inspection stripes 20 are continuously scanned, 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 20, the image of the scan width W is continuously input in the same manner while moving the image of the second inspection stripe 20 in the opposite direction. When an image in the third inspection stripe 20 is acquired, the image is moved in the direction opposite to the direction in which the image in the second inspection stripe 20 is acquired, that is, in the direction in which the image in the first inspection stripe 20 is acquired. While getting the image. In this way, it is possible to shorten a useless processing time by continuously acquiring images. Although the forward (FWD) -backward (BWD) method is used here, the present invention is not limited to this, and a forward (FWD) -forward (FWD) method may be used.

  Then, optical image data (measurement data) in the photomask 101 to be a patterned sample to be inspected is acquired. The measurement data is acquired by the optical image acquisition unit 150. Specifically, the optical image data is acquired as follows. The pattern formed on the photomask 101 is irradiated with light by an appropriate light source 103 disposed above the XYθ table 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. The magnifying optical system 104 may be automatically focused by an unillustrated autofocus mechanism.

  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. The photodiode array 105 is provided with a sensor such as a TDI (Time Delay Integrator) sensor. The TDI sensor images the pattern of the photomask 101 by continuously moving the XYθ table 102 serving as a stage in the X-axis direction. These light source 103, magnifying optical system 104, photodiode array 105, and sensor circuit 106 constitute a high-magnification inspection optical system.

  Measurement data (optical image) output from the sensor circuit 106 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 is, for example, 8-bit unsigned data, and the brightness gradation of each pixel is expressed by, for example, 0 to 255.

  On the other hand, image data (reference data) to be compared with measurement data is created by the development circuit 111 and the reference circuit 112 as follows. Information on the design pattern used when forming the pattern of the photomask 101 is stored in a magnetic disk device 109 which is an example of a storage device (storage unit). Then, the development circuit 111 reads design pattern information from the magnetic disk device 109 through the control computer 110, and converts the design pattern to be the design graphic data of the read photomask 101 into binary or multivalued image data (design image). Data). The image data is sent to the reference circuit 112. The reference circuit 112 performs an appropriate filtering process on the design image data which is the image data of the sent graphic.

  As described above, the optical image data (measurement data) in the photomask 101 serving as the patterned sample to be inspected is acquired by the optical image acquisition unit 150. However, the measurement data as an optical image obtained from the sensor circuit 106 that is a component of the optical image acquisition unit 150 is a state in which a filter is applied due to the resolution characteristics of the magnifying optical system 104, the aperture effect of the photodiode array 105, and the like. In other words, it is in an analog state that continuously changes. For this reason, if the image intensity (shading value) is compared with the design image data which is the image data on the design side of the digital value as it is, an image which is not actually a defect is erroneously determined as a defect (pseudo defect detection). Therefore, the design image data can be adjusted to the measurement data by applying a filter process to the design image data using a photomask 101 and a reference image creation model (optical model) obtained by modeling optical characteristics. Then, the reference data obtained by filtering the design image data and the measurement data obtained from the photomask 101 are compared. This reference data y can be obtained by convolving a design image data u with a reference image creation model function f (optical model function). When this is expressed in the frequency space, it can be expressed as the following expression (1), for example.

  By appropriately setting the coefficient Pi of the reference image creation model function f, reference data matched with measurement data can be created with high accuracy. For this purpose, first, a set of a plurality of coefficients Pi of the optical model function f before the inspection of the photomask 101 is obtained.

FIG. 3 is a flowchart showing main steps of the pattern inspection method according to the first embodiment.
3, the pattern inspection method according to the first embodiment includes a parameter estimation step (S102), an optimum parameter Pk selection step (S104), a reference image (Pk) creation step (S106), and a DB inspection (Pk) step (S108). , Reference image (Pi) creation step (S110), DB inspection (Pi) step (S112), optimum parameter Pm selection step (S114), reference image (Pm) creation step (S116), DB inspection (Pm) step (S118) ), A series of steps of a result output step (S120) is performed.

  In step (S) 102, as a parameter estimation step, the model coefficient estimation circuit 140 receives sample optical image data and sample design image data in which gradation values corresponding to the sample optical image data are defined, and the sample optical image A set of a plurality of Pis of the reference image creation model function f is acquired using the data and the sample design image data. The model coefficient estimation circuit 140 is an example of a coefficient acquisition unit. Here, as the learning sample optical image data, a part of the image of the photomask 101 to be inspected may be acquired by the optical image acquisition unit 150 or may be prepared separately. The sample optical image data is stored in the magnetic disk device 109. For the sample design image data corresponding to the sample optical image data, an image developed by the development circuit 111 from the design data used for pattern formation of the photomask 101 to be inspected may be used, or prepared separately. It doesn't matter. The design image data is stored in the magnetic disk device 109.

FIG. 4 is a conceptual diagram showing an internal configuration of the model coefficient estimation unit in the first embodiment.
In FIG. 4, the model coefficient estimation circuit 140 includes a calculation unit 30, selection units 32 and 34, and a memory 36.

  Here, the sample optical image data is Ai (p), the sample design image data is Bi (p), and the reference image data created by the reference image creation model is f (Param, Bi, p). p is an index indicating a specific pixel on the image. Param is a parameter (coefficient) of the reference image creation model function f. Bi is sample design image data input to the reference image creation model. At this time, the calculation unit 30 calculates (2) and acquires (estimates) a Param that minimizes the function I of the following expression (2).

FIG. 5 is a diagram illustrating an example of a graph of the function I in the first embodiment.
The function I shown in Formula (2) shows a plurality of local minimum values as shown in FIG. In FIG. 5, the coefficient P _i of the reference image creation model function f in the case of the central minimum value, the coefficient P _{i−1 in the} case of one previous minimum value, and the coefficient in the case of one subsequent minimum value. _{Pi + 1} . Furthermore, it is also preferable to perform the calculation of Expression (2) a plurality of times while changing the initial value. The coefficient P _i taking these minimum values is stored in the memory 36. Alternatively, it is stored in the magnetic disk device 109 or the magnetic tape device 115. The memory 36, the magnetic disk device 109, or the magnetic tape device 115 is an example of a storage device. In this way, a set P (P = {P ₁ , P ₂ , P ₃ ,... P _i }) of a plurality of coefficients P _i is acquired. For example, a set P of nearly 100 coefficients P _i is acquired.

In S104, as the optimum parameter Pk selection step, the selection unit 32 selects one coefficient Pk according to a predetermined condition from the set P of a plurality of coefficients P _i . For example, it is preferable to select a coefficient when the minimum value of the function I is obtained.

  In step S106, as a reference image (Pk) creation step, the reference circuit 112 creates reference image data corresponding to the actual optical image data of the photomask 101 that is the patterned sample to be inspected, using the coefficient Pk. The reference image data can be obtained by convolving and integrating the design image data developed by the development circuit 111 corresponding to the actual optical image data and the reference image creation model function f having the coefficient Pk. The reference circuit 112 is an example of a reference image data creation unit.

  In S108, as the DB inspection (Pk) process, first, the optical image acquisition unit 150 acquires actual optical image data by the above-described operation. The actual optical image data output from the sensor circuit 106 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. Then, the comparison circuit 108 inputs the reference image data created by the reference circuit 112 and the acquired actual optical image data, aligns the input actual optical image data and the reference image data, and then performs predetermined processing. The two are compared for each pixel according to the above algorithm, the presence or absence of a defect is determined, and a defect candidate is detected. Here, the pattern determined as a defect as a result of the comparison is stored as a defect candidate in a storage device such as a memory or a magnetic tape device 115 (not shown) together with other comparison results. The comparison circuit 108 is an example of a comparison unit.

In S110, as a reference image (Pi) generating step, the reference circuit 112, the reference for the reference image data including the defect candidate pattern, in the reference image (Pk) creation process of a set P of a plurality of coefficients _{P i} (S106) image Reference image data for the remaining coefficients is created using the remaining coefficients P _i (P _i εP) that are not used for data creation. Reference image data may be obtained by convolving the reference image creation model function f of each coefficient P _i and design image data including the defect candidate pattern deployed in the deployment circuit 111, respectively.

  In S112, as a DB inspection (Pi) process, the comparison circuit 108 compares each reference image data for the remaining coefficients with actual optical image data including a defect candidate pattern. The pattern determined to be defective as a result of the comparison is stored as a defect candidate in a storage device such as a memory or magnetic tape device 115 (not shown) together with other comparison results.

In S114, as the optimum parameter Pm selection step, the selection unit 34 again selects a coefficient that has produced a comparison result in accordance with a predetermined condition from the set P of the plurality of coefficients P _i . For example, it is preferable to use a condition that the number of defects is small as the predetermined condition. In this way, the coefficient Pm of the reference image creation model function f that created the reference image data with the minimum number of defects is selected.

  In S116, as a reference image (Pm) creation step, the reference circuit 112 creates new reference image data for the reference image data including the defect candidate pattern using the coefficient Pm. The reference image data can be obtained by convolving and integrating the design image data including the defect candidate pattern and the reference image creation model function f having the coefficient Pm developed by the development circuit 111. Instead of creating again, a plurality of reference image data created in the reference image (Pk) creation step (S106) and the reference image (Pi) creation step (S110) are not shown, such as a memory, a magnetic disk device 109, or a magnetic tape device 115. Store it in a storage device. It is also preferable to read the created reference image data using the coefficient Pm from the stored storage device.

  In S118, as a DB inspection (Pm) process, the comparison circuit 108 compares the newly created reference image data using the coefficient Pm with actual optical image data including the defect candidate pattern. Instead of the comparison again, it is created using the coefficient Pm from a storage device such as a memory (not shown) or the magnetic tape device 115 in which the comparison results in the DB inspection (Pk) step (S108) and the DB inspection (Pi) step (S112) are stored. It is also preferable to read out the comparison result between the reference image data and the actual optical image data including the defect candidate pattern.

  In S120, as a result output step, the comparison circuit 108 outputs a comparison result according to a predetermined condition among a plurality of comparison results between each reference image data for a plurality of coefficients and actual optical image data including a defect candidate pattern. Output. As the predetermined condition, for example, as described above, a comparison result with reference image data having the smallest number of defects is output. Here, a comparison result that is newly compared between the created reference image data using the coefficient Pm and the actual optical image data including the defect candidate pattern is output. The comparison result is output to the magnetic tape device 115. It is also preferable to display the comparison result on the pattern monitor 118.

  As described above, in the first embodiment, an optimal parameter is found and an optical model is used by re-inspecting an image including a pattern actually determined to be a defect with a reference image created with each parameter. Thus, detection of pseudo defects can be reduced.

  In the above description, what is described as “to part”, “to circuit”, or “to process” can be configured by a computer-operable program. 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 the magnetic disk device 109, the magnetic tape device 115, the FD 116, or a ROM (Read Only Memory). For example, the table control circuit 114, the expansion circuit 111, the reference circuit 112, the model coefficient estimation circuit 140, or the comparison circuit 108 that constitute the arithmetic control unit may be configured by an electrical circuit, or by the control computer 110. It may be realized as software that can be processed. 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. Needless to say, when the reflected light is used, the pixel value obtained from the transmissive part and the pixel value obtained from the light-shielding part are reversed.

  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 or 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.

1 is a conceptual diagram showing a configuration of a pattern inspection apparatus in Embodiment 1. FIG. 6 is a diagram for explaining an optical image acquisition procedure according to Embodiment 1. FIG. FIG. 4 is a flowchart showing main steps of the pattern inspection method in the first embodiment. 3 is a conceptual diagram illustrating an internal configuration of a model coefficient estimation unit according to Embodiment 1. FIG. 6 is a diagram illustrating an example of a graph of a function I in Embodiment 1. FIG.

Explanation of symbols

DESCRIPTION OF SYMBOLS 100 Pattern inspection apparatus 101 Photomask 102 XY (theta) table 103 Light source 104 Magnifying optical system 105 Photodiode array 106 Sensor circuit 107 Position circuit 108 Comparison circuit 109 Magnetic disk apparatus 110 Control computer 111 Expansion circuit 112 Reference circuit 115 Magnetic tape apparatus 140 Model coefficient estimation Circuit 150 Optical Image Acquisition Unit 160 Control Circuit

Claims (5)

Sample optical image data and design image data defining a gradation value corresponding to the sample optical image data are input, and a plurality of coefficients of a predetermined optical model function are obtained using the sample optical image data and the design image data A process of obtaining
Acquiring actual optical image data in the patterned sample to be inspected;
Creating reference image data corresponding to actual optical image data of the sample to be inspected using one of the plurality of coefficients;
Comparing the actual optical image data of the sample to be inspected with the reference image data to detect a defect candidate pattern;
For reference image data including the defect candidate pattern, a step of creating reference image data for the remaining coefficients using the remaining coefficients that are not used for creating the reference image data among the plurality of coefficients,
Comparing each reference image data for the remaining coefficients with actual optical image data including the defect candidate pattern;
Out of a plurality of comparison results between each reference image data for the plurality of coefficients and actual optical image data including the defect candidate pattern, outputting a comparison result in accordance with a predetermined condition;
A pattern inspection method comprising: The pattern inspection method further includes:
Selecting a coefficient used when creating the first reference image data among the plurality of coefficients;
Selecting a coefficient that has produced a comparison result according to the predetermined condition from the plurality of coefficients;
A step of creating new reference image data using a coefficient that has produced a comparison result according to the predetermined condition;
A step of comparing the new reference image data with the actual optical image data including the defect candidate pattern;
With
The pattern inspection method according to claim 1, wherein when the comparison result is output, the comparison result is output again.   3. The pattern inspection method according to claim 1, wherein a condition that the number of defects is small is used as the predetermined condition. Sample optical image data and design image data defining gradation values corresponding to the sample optical image data are input, and a plurality of coefficients of a predetermined optical model function are obtained using the sample optical image data and the design image data A coefficient acquisition unit for acquiring
An optical image acquisition unit for acquiring actual optical image data in the patterned sample to be inspected;
A reference image data creating unit that creates reference image data corresponding to actual optical image data of the sample to be inspected, using one of the plurality of coefficients;
A comparison unit that inputs actual optical image data of the sample to be inspected and compares the reference image data;
With
The reference image data creation unit refers to the reference image data including the pattern determined to be defective as a result of the comparison, using the remaining coefficients that are not used for creating the reference image data among the plurality of coefficients. Create image data,
The said comparison part compares the reference image data produced anew and the actual optical image data containing the pattern determined to be the said defect, The pattern inspection apparatus characterized by the above-mentioned. Sample optical image data and design image data defining gradation values corresponding to the sample optical image data are input, and a plurality of coefficients of a predetermined optical model function are obtained using the sample optical image data and the design image data Acquiring and storing in a storage device;
A process of reading one of the plurality of coefficients from the storage device and using the read coefficient to create reference image data corresponding to actual optical image data of the sample to be inspected;
A process of detecting defect candidate patterns by comparing the actual optical image data acquired from the patterned sample to be inspected and the reference image data;
For the reference image data including the defect candidate pattern, the remaining coefficients that are not used for creating the reference image data among the plurality of coefficients are read from the storage device, and the remaining coefficients are read out using the remaining coefficients that are read. Processing to create reference image data for
A process of comparing each reference image data for the remaining coefficients with actual optical image data including the defect candidate pattern;
Out of a plurality of comparison results between each reference image data for the plurality of coefficients and actual optical image data including the defect candidate pattern, a process of outputting a comparison result according to a predetermined condition;
A program that causes a computer to execute.

Images