Image processing device, optical device, image processing method, and for using optical device

Abstract

To provide an image processing device for taking appropriate measures to a difference in sensitivity caused by a difference in an imaging direction of a pattern, an optical device, an image processing method, and a method for using the optical device.SOLUTION: In an inspection device 1 having an imaging optical system 20, an image processing device 40 comprises: a setting part for setting a first parameter for a first pattern on the basis of a first sample image area being an area including the first pattern extending in an X axis direction in a reference image plane, and setting a second parameter in a second pattern on the basis of a second sample image area being an area including the second pattern extending in a Y axis direction orthogonal to the X axis direction; an acquisition part for acquiring a sample image being a picked-up image obtained by imaging a sample having a third pattern extending in the X axis direction and a fourth pattern extending in the Y axis direction by the prescribed imaging optical system 20; and a processing part for performing prescribed information processing based on the first parameter and the second parameter to the sample image.SELECTED DRAWING: Figure 1

Description

Technical Field

[0001] The present disclosure relates to an image processing apparatus, an optical apparatus, an image processing method, and a method of using an optical apparatus.

Background Art

[0002] Patent Document 1 describes a technique for defect inspection of a photomask by irradiating the photomask with EUV (Extreme Ultra Violet) light.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Non-Patent Documents

[0004]

Non-Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0005] Depending on the design and settings of the optical device, the appearance of the pattern and the appearance of defects in the inspection image may vary depending on the difference in the angle formed between the direction in which the pattern of the photomask extends and the incident direction of the illumination light, or the difference in NA or magnification. For example, even on a pattern surface with the same design, depending on whether the light is incident from the direction in which the pattern extends or the direction orthogonal to the direction in which the pattern extends with respect to the pattern surface, or due to differences in NA or magnification, the appearance of the pattern and the appearance of defects in the inspection image may vary. Also, depending on the difference in NA and magnification in the direction corresponding to each direction on the captured image, even for a pattern surface with the same design or the same defect, the appearance of the pattern and the appearance of defects may vary depending on the imaging direction. Therefore, there may be a need for an inspection that takes into account the differences in sensitivity and appearance caused by the imaging direction of the pattern or the imaging direction of the sample.

[0006] The present disclosure has been made in view of such problems, and provides an image processing apparatus, an optical apparatus, an image processing method, and a method of using an optical apparatus that can appropriately handle differences in sensitivity and appearance caused by the imaging direction of a pattern or the imaging direction of a sample.

Means for Solving the Problems

[0007] An image processing apparatus according to an aspect of the present embodiment sets a first parameter for a first pattern based on a first sample image region that is a region including the first pattern extending in a first direction in a reference image plane, and sets a second parameter for the second pattern based on a second sample image region that is a region including the second pattern extending in a second direction orthogonal to the first direction in the reference image plane. The apparatus includes a setting unit, an acquisition unit that acquires a sample image that is the captured image of a sample having a third pattern extending in the first direction and a fourth pattern extending in the second direction in the captured image when the plane of the captured image is the reference image plane by a predetermined imaging optical system, and a processing unit that performs predetermined information processing on the sample image based on the first parameter and the second parameter.

[0008] In the above-described image processing apparatus, the setting unit sets the first parameter to include a threshold value used for determining the presence or absence of a defect in the third pattern included in the sample image, and sets the second parameter to include a threshold value used for determining the presence or absence of the defect in the fourth pattern included in the sample image. The processing unit may perform the predetermined information processing including determining the presence or absence of the defect in the third pattern and the fourth pattern included in the sample image.

[0009] In the above-described image processing apparatus, the sample image includes both the third pattern and the fourth pattern, and the processing unit may perform the predetermined information processing including determining the presence or absence of the defect in the third pattern and the fourth pattern included in the sample image.

[0010] In the above-described image processing apparatus, the setting unit may set the threshold value for a plurality of types of physical quantities regarding the information of the sample image.

[0011] In the above-described image processing apparatus, the setting unit may set at least one of the type and the number of the physical quantities for which the threshold value is defined as the first parameter to be different from the physical quantity for which the threshold value is defined as the second parameter.

[0012] In the above-described image processing apparatus, at least one of the first sample image region and the second sample image region may be a region included in an image generated based on the design data of the sample or the design data of the pattern formed on the sample.

[0013] In the above-described image processing apparatus, the first sample image region may be a region included in the captured image of the object having the first pattern by the predetermined imaging optical system.

[0014] In the above-described image processing apparatus, the first sample image region and the second sample image region may be regions included in the captured image of the object having the first pattern and the second pattern by the predetermined imaging optical system.

[0015] In the above-described image processing apparatus, the first sample image region and the second sample image region are regions included in the captured image of the object having the first pattern by the predetermined imaging optical system. The orientation of the object with respect to the predetermined imaging optical system at the time of capturing the captured image including the first sample image region and the orientation of the object with respect to the predetermined imaging optical system at the time of capturing the captured image including the second sample image region may differ by 90° in the principal plane of the object.

[0016] In the above-described image processing apparatus, the predetermined imaging optical system captures an image by oblique incident illumination on the object, and the first sample image region may be included in the captured image when the angle formed by the direction in which the principal axis of the oblique incident illumination is projected onto the upper surface of the object and the first direction is a predetermined angle.

[0017] In the above-described image processing apparatus, the predetermined imaging optical system captures an image by oblique incident illumination on the object, and the first sample image region and the second sample image region may be included in the captured image when the angle formed by the direction in which the principal axis of the oblique incident illumination is projected onto the upper surface of the object and the first direction is a predetermined angle.

[0018] In the above-described image processing apparatus, the predetermined imaging optical system captures an image by oblique incident illumination on the sample, and the sample image may be a captured image by the predetermined imaging optical system when the angle formed by the direction in which the principal axis of the oblique incident illumination is projected onto the upper surface of the sample and the first direction is a predetermined angle.

[0019] In the above-described image processing apparatus, the sample may include an anamorphic mask.

[0020] In the above-described image processing apparatus, the acquisition unit may acquire sample images in which the number of pixels binned in the first direction and the second direction is different.

[0021] In the above-described image processing apparatus, the predetermined imaging optical system may have different NAs in the first direction and the second direction.

[0022] In the above-described image processing apparatus, the setting unit sets the first parameter to include a correction value of the luminance of pixels belonging to the third pattern included in the sample image, sets the second parameter to include a correction value of the luminance of pixels belonging to the fourth pattern included in the sample image, and the processing unit may perform the predetermined information processing including image correction of the sample image.

[0023] The optical apparatus according to one aspect of the present embodiment includes an illumination optical system that illuminates the sample, the predetermined imaging optical system that images the illuminated sample, and the image processing apparatus described above.

[0024] An image processing method according to one aspect of the present embodiment includes a step of setting a first parameter for the first pattern based on a first sample image region that is a region including a first pattern extending in a first direction in a reference image plane, a step of setting a second parameter for the second pattern based on a second sample image region that is a region including a second pattern extending in a second direction orthogonal to the first direction in the reference image plane, a step of obtaining a sample image that is the captured image obtained by capturing, with a predetermined imaging optical system, a sample having a third pattern extending in the first direction and a fourth pattern extending in the second direction in the captured image when the plane of the captured image is the reference image plane, and a step of performing predetermined information processing on the sample image based on the first parameter and the second parameter.

[0025] A method of using an optical apparatus according to one aspect of the present embodiment includes a step of illuminating the sample, a step of imaging the illuminated sample, and the image processing method described above.

Advantages of the Invention

[0026] According to the present disclosure, it is possible to provide an image processing apparatus, an optical apparatus, an image processing method, and a method of using an optical apparatus that can appropriately handle differences in sensitivity caused by the imaging direction of a pattern.

Brief Description of the Drawings

[0027]

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Mode for Carrying Out the Invention

[0028] Hereinafter, embodiments of the present disclosure will be described with reference to the drawings. The following description shows preferred embodiments of the present disclosure, and the scope of the present disclosure is not limited to the following embodiments. In the following description, those with the same reference numerals indicate substantially the same content.

[0029] (Embodiment 1) An image processing apparatus, an optical apparatus, an image processing method, and a method of using an optical apparatus according to Embodiment 1 will be described. First, in the <inspection apparatus>, as an example of the optical apparatus, the inspection apparatus will be described. Next, in the <pattern>, the pattern of a sample that can be an inspection target or the like will be described. Next, in the <image processing apparatus>, the image processing apparatus provided in the optical apparatus will be described. Next, in the <image processing method> and the <inspection method>, an inspection method as an example of an image processing method using the image processing apparatus and a method of using the optical apparatus will be described.

[0030] Note that the image processing apparatus and the image processing method, which are examples of the present disclosure, may be used for an inspection apparatus as described in the following embodiments, but are not limited thereto. For example, the image processing apparatus and the image processing method, which are examples of the present disclosure, may be used as a device (review device) that displays an image (captured image) obtained as a result of illuminating a sample on a display or the like.

[0031] <Inspection apparatus> FIG. 1 is a configuration diagram illustrating an inspection apparatus 1 according to Embodiment 1. The inspection apparatus 1 includes an illumination optical system 10, an imaging optical system 20, and an image processing apparatus 40. The illumination optical system 10 illuminates a sample 50 using illumination light L11. Note that the illumination optical system 10 may illuminate an object used for acquiring a first sample image region and a second sample image region, which will be described later, using the illumination light L11, similar to the sample 50. The illumination optical system 10 includes, for example, a light source 11, an elliptical mirror 12, an elliptical mirror 13, and a reduction mirror 14. The imaging optical system 20 captures a captured image of the sample 50 illuminated by the illumination light L11. Note that the captured image of the sample 50 may be referred to as a sample image. The imaging optical system 20 includes, for example, a perforated concave mirror 21, a convex mirror 22, and a detector 23. The perforated concave mirror 21 and the convex mirror 22 constitute a Schwarzschild magnification optical system. Note that the illumination optical system 10 and the imaging optical system 20 may further include optical members other than those described above, or any of the above-described optical members may be omitted.

[0032] Here, for the convenience of explaining the inspection apparatus 1, an XYZ orthogonal coordinate system is introduced. For example, a plane parallel to the stage surface of the stage 52 on which the sample 50 is placed is defined as the XY plane, and the direction orthogonal to the stage surface is defined as the Z-axis direction. The +Z-axis direction is, for convenience, referred to as the upward direction, and the -Z-axis direction is referred to as the downward direction. Note that the upward and downward directions are for the convenience of explaining the inspection apparatus 1 and do not indicate the direction in which the actual inspection apparatus 1 is placed.

[0033] The light source 11 generates illumination light L11. The illumination light L11 includes, for example, EUV light of 13.5 nm, which is the same as the exposure wavelength of the EUV mask that is the sample 50. The illumination light L11 generated from the light source 11 is reflected by the ellipsoidal mirror 12. The illumination light L11 reflected by the ellipsoidal mirror 12 travels while being narrowed down and is focused at the focus point IF1. The focus point IF1 is arranged at a position conjugate to the upper surface 51 of the sample 50.

[0034] After passing through the focus point IF1, the illumination light L11 spreads while traveling and is incident on a reflecting mirror such as the ellipsoidal mirror 13. The illumination light L11 incident on the ellipsoidal mirror 13 is reflected by the ellipsoidal mirror 13, travels while being narrowed down, and is incident on the dropping mirror 14. That is, the ellipsoidal mirror 13 makes the illumination light L11 incident on the dropping mirror 14 as convergent light. The dropping mirror 14 is arranged above the sample 50. The illumination light L11 incident on and reflected by the dropping mirror 14 is incident on the sample 50. That is, the dropping mirror 14 makes the illumination light L11 incident on the sample 50.

[0035] The ellipsoidal mirror 13 focuses the illumination light L11 on the sample 50. When the illumination light L11 illuminates the sample 50, the illumination optical system 10 is installed so as to form an image of the light source 11 on the upper surface 51 of the sample 50. Therefore, the illumination optical system 10 is critical illumination. Thus, the illumination optical system 10 illuminates the sample 50 using critical illumination by the illumination light L11 generated by the light source 11.

[0036] The sample 50 is placed on the stage 52. The illumination light L11 is incident on the sample 50 from a direction inclined from the Z-axis direction. That is, the illumination light L11 is incident obliquely on the sample 50 as oblique incidence illumination. As such oblique incidence illumination, the illumination light L11 may illuminate the sample 50.

[0037] The stage 52 is an XYZ drive stage. By moving the stage 52 in the X-axis direction and the Y-axis direction, a desired region of the sample 50 can be illuminated. Further, by moving the stage 52 in the Z-axis direction, focus adjustment can be performed. Also, the stage 52 may be rotated about the X-axis, Y-axis, and Z-axis as rotation axes. Note that instead of moving and rotating the stage 52 along the X-axis direction, Y-axis direction, and Z-axis direction, the illumination optical system 10 and the imaging optical system 20 may be moved and rotated.

[0038] The illumination light L11 from the light source 11 illuminates the inspection region of the sample 50. Incident from a direction inclined with respect to the Z-axis direction, the reflected light L12 reflected by the sample 50 is incident on the perforated concave mirror 21. A hole 21a is provided at the center of the perforated concave mirror 21.

[0039] The reflected light L12 reflected by the perforated concave mirror 21 is incident on the convex mirror 22. The convex mirror 22 reflects the reflected light L12 incident from the perforated concave mirror 21 toward the hole 21a of the perforated concave mirror 21. The reflected light L12 that has passed through the hole 21a is detected by the detector 23. The detector 23 may be a detector 23 including a TDI (Time Delay Integration) sensor. The detector 23 acquires image data of the sample 50. The detector 23 includes a plurality of imaging elements arranged in a line in one direction. The line-shaped image data captured by the plurality of imaging elements arranged in a line is referred to as one-dimensional image data or one frame. The detector 23 acquires a plurality of one-dimensional image data by scanning in a direction orthogonal to one direction. The imaging element is, for example, a CCD (Charge Coupled Device). Note that the imaging element is not limited to a CCD.

[0040] In this way, the imaging optical system 20 condenses the reflected light L12 from the sample 50 illuminated by the illumination light L11, and the condensed reflected light L12 is detected by the detector 23 to acquire the image data of the sample 50. The image data is, for example, one-dimensional image data. Note that the imaging optical system 20 may condense the reflected light L12 from the object illuminated by the illumination light L11, and the condensed reflected light L12 may be detected by the detector 23 to acquire the image data of the object.

[0041] The reflected light L12 contains information such as defects of the sample 50. The specular reflection light of the illumination light L11 incident on the sample 50 from a direction inclined with respect to the Z-axis direction is detected by the imaging optical system 20. When there is a defect in the sample 50, the defect is observed as a dark image. Such an observation method is called bright-field observation. A plurality of one-dimensional image data of the sample 50 acquired by the detector 23 is output to the image processing apparatus 40 and processed into two-dimensional image data.

[0042] The image processing apparatus 40 is connected to the imaging optical system 20 by a signal line or wirelessly. The image processing apparatus 40 receives the image data of the sample 50 from the detector 23 in the imaging optical system 20. The image processing apparatus 40 performs image processing on the image data of the sample 50 received from the detector 23 as a two-dimensional captured image. The image processing apparatus 40 inspects the sample 50 using the image-processed captured image.

[0043] With such a configuration, the inspection apparatus 1 inspects defects, contamination, etc. of the sample 50. The sample 50 is, for example, an EUV mask corresponding to EUV light. Note that the sample 50 is not limited to an EUV mask. The sample 50 may be a photomask corresponding to illumination light L11 having other wavelengths, or a semiconductor substrate. The photomask has a pattern.

[0044] <Pattern> Next, the pattern formed on the sample 50 will be described. As an example, the mask pattern of a photomask will be described. Note that the pattern is not limited to the mask pattern, and may be a pattern formed on a semiconductor substrate or the like. Hereinafter, the sample 50 which is a target for performing predetermined information processing such as determination of the presence or absence of defects will be described, but the same applies to the object used for acquiring the first sample image region and the second sample image region described later. Here, the object used for acquiring the first sample image region and the second sample image region may be the same object as the sample 50 which is a target for performing predetermined information processing such as determination of the presence or absence of defects, or may be a different object.

[0045] FIG. 2 is a diagram illustrating the mask pattern MP of the sample 50 according to Embodiment 1. As shown in FIG. 2, the sample 50 has a mask pattern MP. The mask pattern MP may include a manufacturing-induced error called line edge roughness (hereinafter referred to as LER) at the edge portion.

[0046] FIG. 3 is a diagram illustrating an image captured such that the mask pattern MP of the sample 50 according to Embodiment 1 extends in the first direction. FIG. 4 is a diagram illustrating an image captured such that the mask pattern MP of the sample 50 according to Embodiment 1 extends in the second direction. As shown in FIG. 3, in the image G01, the mask pattern MP extends in the first direction. As shown in FIG. 4, in the image G02, the mask pattern MP extends in the second direction orthogonal to the first direction.

[0047] Here, an αβ orthogonal coordinate system is introduced in the plane of the image plane. For example, the image plane may be referred to as a reference image plane. In the plane of the image plane, the vertical direction is the α-axis direction, and the horizontal direction is the β-axis direction. The α-axis direction is called the first direction, and the β-axis direction is called the second direction. Then, the mask pattern MP in the image G01 extends in the α-axis direction, and the mask pattern MP in the image G02 extends in the β-axis direction.

[0048] The α-axis direction and the β-axis direction may or may not correspond to the X-axis direction and the Y-axis direction on the stage 52. For example, the α-axis direction and the β-axis direction in the reference image plane are made to correspond to the X-axis direction and the Y-axis direction on the stage 52. Therefore, when the mask pattern MP shown in FIG. 2 is arranged along the X-axis direction on the stage 52, it is imaged along the α-axis direction as in the image G01 of FIG. 3. On the other hand, when the mask pattern MP shown in FIG. 2 is arranged along the Y-axis direction on the stage 52, it is imaged along the β-axis direction as in the image G02 of FIG. 4. Thus, by arranging the same mask pattern MP along the X-axis direction or the Y-axis direction on the stage 52, it is imaged along the α-axis direction or the β-axis direction.

[0049] Hereinafter, for convenience of explanation, when the mask pattern MP of the sample 50 is arranged so as to extend in the X-axis direction of the stage 52, it is assumed that the mask pattern MP is imaged so as to extend in the α-axis direction. Also, when the mask pattern MP is arranged so as to extend in the Y-axis direction of the stage 52, it is assumed that the mask pattern MP is imaged so as to extend in the β-axis direction.

[0050] Note that depending on the number and type of optical members constituting the imaging optical system 20, when the mask pattern MP is arranged so as to extend in the X-axis direction of the stage 52, the mask pattern MP may be imaged so as to extend in the β-axis direction, and when the mask pattern MP is arranged so as to extend in the Y-axis direction of the stage 52, the mask pattern MP may be imaged so as to extend in the α-axis direction.

[0051] When imaging the sample 50, the mask pattern MP imaged so as to extend in the α-axis direction is called the first pattern 71 or the third pattern 73. For example, among the mask patterns MP extending in the α-axis direction, which is the first direction in the reference image plane, the mask pattern MP in the first sample image including the first sample image region to be described later is the first pattern 71. Also, for example, among the mask patterns MP extending in the α-axis direction, which is the first direction in the reference image plane, the mask pattern MP in the sample image obtained by imaging the object for performing predetermined information processing such as determination of the presence or absence of defects to be described later is the third pattern 73.

[0052] When imaging the sample 50, the mask pattern MP imaged so as to extend in the β-axis direction is called the second pattern 72 or the fourth pattern. For example, among the mask patterns MP extending in the β-axis direction, which is the second direction orthogonal to the first direction in the reference image plane, the mask pattern MP in the second sample image including the second sample image region to be described later is the second pattern 72. Also, for example, among the mask patterns MP extending in the β-axis direction, which is the second direction orthogonal to the first direction in the reference image plane, the mask pattern MP in the sample image obtained by imaging the object for performing predetermined information processing such as determination of the presence or absence of defects to be described later is the fourth pattern 74.

[0053] For example, the images G01 and G02 may be images of the sample 50 captured by an imaging optical system 20 with different numerical apertures (hereinafter referred to as NA) in the X-axis direction and the Y-axis direction. Specifically, the image G01 may be an image captured when the sample 50 having the mask pattern MP is placed on the stage 52 such that the mask pattern MP extends in the X-axis direction. That is, the image G01 may be an image captured when the sample 50 having the mask pattern MP is placed on the stage 52 so as to have the first pattern 71. The image G02 may be an image captured when the sample 50 having the mask pattern MP is placed on the stage 52 such that the mask pattern MP extends in the Y-axis direction. That is, the image G02 may be an image captured when the sample 50 having the mask pattern MP is placed on the stage 52 so as to have the second pattern 72. The imaging optical system 20 may be an imaging optical system with different NAs in a first direction and a second direction orthogonal to the first direction when the captured image is used as a reference image plane. Further, the imaging optical system may be an imaging optical system with different imaging magnifications in a first direction and a second direction orthogonal to the first direction when the captured image is used as a reference image plane.

[0054] Also, for example, the images G01 and G02 may be captured with the angle formed by the main axis of the oblique incidence illumination and the direction in which the mask pattern MP extends changed. For example, the image G01 may be an image captured such that the angle formed by the direction in which the main axis of the oblique incidence illumination is projected onto the upper surface of the sample 50 and the X-axis direction in which the mask pattern MP extends is a predetermined angle. The image G02 may have the main axis of the oblique incidence illumination in the same direction as that of the image G01. In this case, the mask pattern MP extends in the Y-axis direction, and the image is captured such that the angle formed by the direction in which the main axis of the oblique incidence illumination is projected onto the upper surface of the sample 50 and the Y-axis direction in which the mask pattern MP extends is an angle approximately 90° different from the predetermined angle. Here, the approximate 0° and approximate 90° mean not only the exact 0° and 90° but also the ranges including measurement and device errors of 0° and 90°. Note that angles such as 0° and 90° shown below may be used in the meaning including the approximate even when the approximate is omitted.

[0055] Further, for example, the images G01 and G02 may be images obtained by imaging each mask pattern MP of a sample (for example, FIG. 6 described later) having both a mask pattern MP extending in the X-axis direction and a mask pattern MP extending in the Y-axis direction by oblique incidence illumination.

[0056] As shown in FIGS. 3 and 4, the magnitude of the influence of LER on the image changes depending on the orientation of the mask pattern MP during imaging. As an example, since the NA of the imaging optical system 20 used in an inspection apparatus for a photomask using EUV light is different in the X-axis direction and the Y-axis direction, the resolution may change in the α-axis direction and the β-axis direction of the images G01 and G02. For example, as in the first pattern 71 shown in FIG. 3, the resolution when the mask pattern MP is viewed along the α-axis direction (for example, the substantially 0° direction), and as in the second pattern 72 shown in FIG. 4, the mask pattern MP is viewed along the β-axis direction (for example, the 90° direction). The appearance of the mask pattern MP is different from the resolution in this case. As a result, even for defects of the same shape, the detection sensitivity changes depending on whether the defect is at the edge in the α-axis direction of the pattern or at the edge in the β-axis direction of the pattern.

[0057] Therefore, the image processing apparatus 40 according to the present embodiment detects the mask pattern MP in each of the α-axis direction and the β-axis direction so that the sensitivity in each direction can be independently adjusted. Specifically, as will be described later, the setting unit 42 of the image processing apparatus 40 independently sets parameters used for predetermined information processing including determination of the presence or absence of defects in each direction for each direction. As a result, different algorithms can be set for each direction, and the sensitivity difference for each direction can be reduced.

[0058] <Image Processing Apparatus> Next, the image processing apparatus 40 will be described. FIG. 5 is a block diagram illustrating the image processing apparatus 40 according to Embodiment 1. As shown in FIG. 5, the image processing apparatus 40 includes an acquisition unit 41, a setting unit 42, and a processing unit 43. The acquisition unit 41, the setting unit 42, and the processing unit 43 have functions as acquisition means, setting means, and processing means. Note that the image processing apparatus 40 may further include a unit having other functions such as a storage unit serving as storage means. The processing unit 43 may be at least one of a determination unit 43a and an image correction unit 43b described later. The determination unit 43a and the image correction unit 43b have functions as determination means and image correction means.

[0059] The acquisition unit 41 acquires a first sample image region and a second sample image region. The first sample image region and the second sample image region may actually be acquired from an image obtained by imaging an object prepared for acquisition of the first sample image region and the second sample image region, or may be acquired from an image formed from design data. An image for acquiring the first sample image region and the second sample image region is called a sample image. Therefore, the sample image may be an image captured by the imaging optical system 20 or an image based on design data.

[0060] FIGS. 6 to 8 are diagrams illustrating mask patterns MP1 and MP2 of samples 50a to 50c for sample images according to Embodiment 1. As shown in FIGS. 6 to 8, the samples 50a to 50c for sample images have at least one of the mask patterns MP1 and MP2. The samples 50a to 50c for sample images may be referred to as objects in order to distinguish them from the sample 50 for sample images. As shown in FIG. 6, the sample 50a for sample images has the mask patterns MP1 and MP2. As shown in FIG. 7, the sample 50b for sample images has the mask pattern MP1. As shown in FIG. 8, the sample 50c for sample images has the mask pattern MP2.

[0061] FIG. 9 is a diagram illustrating a first sample image G11 acquired by an acquisition unit 41 in the image processing apparatus 40 according to Embodiment 1. As shown in FIG. 9, the first sample image G11 includes a first pattern 71 extending in the α-axis direction within the plane of the image plane. The region including the first pattern 71 is called a first sample image region. Therefore, the first sample image G11 includes the first sample image region. The acquisition unit 41 may acquire the first sample image G11 and the first sample image region from an image obtained by imaging a sample 50a for a sample image, or may acquire the first sample image G11 and the first sample image region from an image obtained by imaging a sample 50b for a sample image. That is, the first sample image region may be a region included in an image obtained by imaging an object having the first pattern 71 with a predetermined imaging optical system 20.

[0062] FIG. 10 is a diagram illustrating a second sample image G12 acquired by the acquisition unit 41 in the image processing apparatus 40 according to Embodiment 1. As shown in FIG. 10, the second sample image G12 includes a second pattern 72 extending in the β-axis direction within the plane of the image plane. The region including the second pattern 72 is called a second sample image region. Therefore, the second sample image G12 includes the second sample image region. The acquisition unit 41 may acquire the second sample image G12 and the second sample image region from an image obtained by imaging a sample 50a for a sample image, or may acquire the second sample image G12 and the second sample image region from an image obtained by imaging a sample 50c for a sample image. That is, the second sample image region may be a region included in an image obtained by imaging an object having the second pattern 72 with a predetermined imaging optical system 20.

[0063] When the acquisition unit 41 acquires the first sample image G11 and the first sample image area by obliquely incident illumination on the sample 50a or 50b having the first pattern 71 on the stage 52, the direction in which the main axis of the obliquely incident illumination is projected onto the upper surface of the sample 50a and the X-axis direction (i.e., the first direction or the α-axis direction) in which the first pattern 71 extends may be set so that the angle formed therebetween is a predetermined angle, and the first sample image G11 may be acquired. That is, the predetermined imaging optical system 20 captures an image by obliquely incident illumination on the object. The first sample image area is included in the captured image when the angle formed by the direction in which the main axis of the obliquely incident illumination is projected onto the upper surface of the object and the first direction is a predetermined angle.

[0064] Further, when the acquisition unit 41 acquires the second sample image G12 and the second sample image area by obliquely incident illumination on the sample 50a or 50c having the second pattern 72, the direction in which the main axis of the obliquely incident illumination is projected onto the upper surface of the sample 50a and the Y-axis direction (i.e., the second direction and the β-axis direction) in which the second pattern 72 extends may be set so that the angle formed therebetween is an angle different by 90° from the predetermined angle, and the second sample image G12 may be acquired. Also, the predetermined imaging optical system 20 captures an image by obliquely incident illumination on the object. The first sample image area and the second sample image area may be included in the captured image when the angle formed by the direction in which the main axis of the obliquely incident illumination is projected onto the upper surface of the object and the first direction is a predetermined angle.

[0065] Furthermore, the acquisition unit 41 may acquire the second sample image G12 and the second sample image area from the image obtained by imaging the sample 50b. That is, the sample 50b is rotated 90° around the Z axis on the stage 52. Thereby, the first pattern 71 can be imaged as the second pattern. Similarly, the acquisition unit 41 may acquire the first sample image G11 and the first sample image area from the image obtained by imaging the sample 50c. That is, the sample 50c is rotated 90° around the Z axis on the stage 52. Thereby, the second pattern 72 can be imaged as the first pattern. Thus, the first sample image area and the second sample image area may be areas included in the captured image by the predetermined imaging optical system 20 of the object having the first pattern. The orientation of the object with respect to the predetermined imaging optical system 20 at the time of capturing the captured image including the first sample image area and the orientation of the object with respect to the predetermined imaging optical system 20 at the time of capturing the captured image including the second sample image area differ by 90° in the main plane of the object.

[0066] In addition, when the acquisition unit 41 acquires the first sample image G11, the first sample image area, the second sample image G12, and the second sample image area by oblique incident illumination on the sample 50a having the first pattern 71 and the second pattern 72 on the stage 52, the angle formed by the direction in which the main axis of the oblique incident illumination is projected onto the upper surface of the sample 50a and the X-axis direction (i.e., the first direction or the α-axis direction) is set to a predetermined angle, and the first sample image G11, the first sample image area, the second sample image G12, and the second sample image area may be acquired. That is, the first sample image area and the second sample image area may be areas included in the captured image by the predetermined imaging optical system 20 of the object having the first pattern 71 and the second pattern 72.

[0067] When acquiring the first sample image G11, the first sample image region, the second sample image G12, and the second sample image region by oblique incident illumination on the sample 50a having the first pattern 71 and the second pattern 72, the orientation of the object with respect to the predetermined imaging optical system 20 at the time of imaging the imaging image including the first sample image region and the orientation of the object with respect to the predetermined imaging optical system 20 at the time of imaging the imaging image including the second sample image region may be substantially the same. Alternatively, the imaging image including the first sample image region and the imaging image including the second sample image region may be the same imaging image.

[0068] Note that the acquisition unit 41 may acquire at least one of the first sample image G11 and the second sample image G12 based on the design data of the sample 50 or the design data of the pattern formed on the sample 50.

[0069] FIG. 11 is a diagram illustrating the captured image G13 acquired by the acquisition unit 41 in the image processing apparatus 40 according to the first embodiment. As shown in FIG. 11, the acquisition unit 41 acquires the captured image G13. The captured image G13 includes a third pattern 73 extending in the α-axis direction and a fourth pattern 74 extending in the β-axis direction in the in-plane of the image plane in the captured image G13 with the plane of the captured image G13 as a reference image plane. The captured image G13 is a sample image obtained by imaging a sample having the third pattern 73 and the fourth pattern 74. Similar to the first pattern 71, the third pattern 73 is a mask pattern MP1 that is imaged so as to extend in the α-axis direction when the sample is imaged. Similar to the second pattern 72, the fourth pattern 74 is a mask pattern MP2 that is imaged so as to extend in the β-axis direction when the sample is imaged.

[0070] If predetermined information processing can be performed using the first parameter and the second parameter described below, the pattern widths and pitch intervals between the first pattern 71 and the third pattern 73 may be the same or different. Similarly, the pattern widths and pitch intervals between the second pattern 72 and the fourth pattern 74 may be the same or different. Here, the pattern widths and pitch intervals being the same or different may mean by comparison of the pattern widths and pitch intervals of the patterns physically formed on the sample, or may mean by comparison of the pattern widths and pitch intervals in the patterns reflected in the sample image and drawn as images in the first sample image region and the second sample image region.

[0071] The captured image G13 is, for example, a captured image of a sample on which both a pattern extending in one direction and a pattern extending in a direction substantially 90° different therefrom are formed on the sample surface. Note that the pattern extending in one direction and the pattern extending in a direction 90° different therefrom may have different extending directions but may be physically formed with substantially the same pattern width and pitch interval, or may be formed such that, like an anamorphic mask, their extending directions and physical pattern widths and pitch intervals are different, but their pattern widths and pitch intervals appear substantially the same on the captured image plane. The captured image G13 may be, for example, an image obtained by capturing the sample 50a for the sample image shown in FIG. 6. In that case, the sample 50a is an object to be subjected to predetermined information processing such as defect determination and is also an object for obtaining the first sample image region and the second sample image region. Also, the third pattern 73 is the first pattern, and the fourth pattern 74 is the second pattern. Hereinafter, the captured image G13 will be described as a sample image obtained by capturing the sample 50a.

[0072] The captured image G13 may include both the third pattern 73 and the fourth pattern 74. The acquisition unit 41 acquires the captured image G13 obtained by capturing the sample 50a including the third pattern 73 and the fourth pattern 74. The acquisition unit 41 may acquire the captured image G13 captured by the imaging optical system 20 having different NAs in the X-axis direction and the Y-axis direction.

[0073] When the acquisition unit 41 acquires the captured image G13 by obliquely incident illumination on the sample 50a having the third pattern 73, the angle formed by the direction in which the main axis of the obliquely incident illumination is projected onto the upper surface of the sample 50a and the X-axis direction (i.e., the first direction and the α-axis direction) may be set to a predetermined angle, and the captured image G13 may be acquired. That is, the predetermined imaging optical system 20 captures an image by obliquely incident illumination on the sample 50a. The sample image is a captured image obtained by the predetermined imaging optical system 20 when the angle formed by the direction in which the main axis of the obliquely incident illumination is projected onto the upper surface of the sample and the first direction is a predetermined angle.

[0074] FIGS. 12 and 13 are graphs illustrating the relationship between the difference signal and the appearance probability between predetermined pixels in the captured image G13 acquired by the acquisition unit 41 in the image processing apparatus 40 according to the first embodiment. The horizontal axis represents the difference signal, and the vertical axis represents the appearance probability. FIG. 12 shows the difference signal between predetermined pixels of the third pattern 73 in the captured image G13, and FIG. 13 shows the difference signal of the fourth pattern 74 in the captured image G13.

[0075] As shown in FIGS. 12 and 13, the appearance probability of the difference signal of the third pattern 73 extends over a wider range than the appearance probability of the difference signal of the fourth pattern 74. That is, it shows that the third pattern 73 is more affected by noise or the like than the fourth pattern. Thus, the appearance probability distribution may be created from the histogram of the difference signals obtained from the patterns in the α-axis direction and the β-axis direction in the captured image G13. And the influence of noise in each direction may be predicted from the created appearance probability distribution of the difference signal. Thereby, the defect detection sensitivity in each direction can be optimized. For example, when the third pattern 73 is more affected by noise or the like than the fourth pattern, the threshold for defect detection of the third pattern is relaxed compared to the fourth pattern.

[0076] The setting unit 42 sets the first parameter for the first pattern 71 based on the first sample image area. The first parameter may include parameters for detecting the first pattern 71, or may include parameters for defect detection of the first pattern 71. The setting unit 42 may set the first parameter for the first pattern 71 based on the line edge roughness (hereinafter referred to as LER) distribution in the first sample image area. Note that the setting unit 42 is not limited to the LER distribution in the first sample image area, and may set the first parameter for the first pattern 71 based on the central luminance, average luminance, line width, etc. of the first pattern 71 in the first sample image area.

[0077] The setting unit 42 may set the first parameter to include a threshold value used for determining the presence or absence of a defect in the third pattern 73 included in the captured image G13 (sample image as described above, the same applies hereinafter). Specifically, the setting unit 42 may set the first parameter to include a threshold value used for defect inspection for the third pattern 73. Further, the setting unit 42 may set the first parameter to include a threshold value used for defect inspection based on the luminance difference for the third pattern 73. The luminance difference includes the difference between the luminance of the first pattern 71 in the first sample image G11 and the luminance of the third pattern 73 in the captured image G13.

[0078] Also, the setting unit 42 sets the second parameter for the second pattern 72 based on the second sample image area. The second parameter may include parameters for detecting the second pattern 72, or may include parameters for defect detection of the second pattern 72. The setting unit 42 may set the second parameter for the second pattern 72 based on the LER distribution in the second sample image area. Note that the setting unit 42 is not limited to the LER distribution in the second sample image area, and may set the second parameter for the second pattern 72 based on the central luminance, average luminance, line width, etc. of the second pattern 72 in the second sample image area.

[0079] The setting unit 42 may set the second parameter to include a threshold value used for determining the presence or absence of defects in the fourth pattern 74 included in the captured image G13 (the sample image as described above, and the same applies hereinafter). Specifically, the setting unit 42 may set the second parameter to include a threshold value used for defect inspection for the fourth pattern 74. Further, the setting unit 42 may set the second parameter to include a threshold value used for defect inspection based on the luminance difference for the fourth pattern 74. The luminance difference includes the difference between the luminance of the second pattern 72 in the second sample image G12 and the luminance of the fourth pattern 74 in the captured image G13.

[0080] The setting unit 42 may set the threshold value for a plurality of types of physical quantities regarding the information of the captured image G13. The setting unit 42 may set at least one of the type and the number of physical quantities for which the threshold value is defined as the first parameter to be different from the physical quantity for which the threshold value is defined as the second parameter. As described above, for example, when the third pattern 73 is more affected by noise or the like than the fourth pattern, it may be preferable to relax the threshold value for defect detection of the third pattern more than that of the fourth pattern. For this purpose, the setting unit 42 may set the number of physical quantities that are the threshold values when setting the second parameter as the threshold value used for determining the presence or absence of defects in the fourth pattern 74 to be larger than the number of physical quantities that are the threshold values when setting the first parameter as the threshold value used for determining the presence or absence of defects in the third pattern 73. The physical quantity includes the LER of the pattern, the center luminance of the pattern, the average luminance of the pattern, the line width of the pattern, the luminance difference, etc., and may be selected from these groups.

[0081] The processing unit 43 performs predetermined information processing on the captured image G13 based on the first parameter and the second parameter. The predetermined information processing may include performing a predetermined determination and performing a predetermined image correction. The predetermined determination may include determining the presence or absence of a defect. The processing unit 43 performs predetermined information processing including determining the presence or absence of a defect in the third pattern 73 and the fourth pattern 74 included in the captured image G13. In this case, the processing unit 43 may sometimes be referred to as a determination unit 43a instead of the processing unit 43. The processing unit 43 (determination unit 43a) may perform predetermined information processing including determining the presence or absence of a defect in at least any one of the third pattern 73 and the fourth pattern 74 included in the captured image G13.

[0082] Also, the processing unit 43 may perform predetermined information processing including image correction of the captured image G13 to correct and mitigate the difference in sensitivity expected in the third pattern 73 and the fourth pattern 74 included in the captured image G13. In this case, the processing unit 43 may sometimes be referred to as an image correction unit 43b instead of the processing unit 43. In this case, for example, the setting unit 42 sets the first parameter as a correction value of the luminance of the pixels belonging to the third pattern 73 included in the captured image G13, and sets the second parameter as a correction value of the luminance of the pixels belonging to the fourth pattern 74 included in the captured image G13. The processing unit 43 (image correction unit 43b) performs predetermined information processing including image correction to correct the luminance for at least a part of the pixels belonging to the third pattern 73 or the fourth pattern 74 included in the captured image G13 based on such first and second parameters. Note that the setting unit 42 may set the first parameter and the second parameter by specifying the correction values of the luminance of the pixels belonging to the first pattern 71 and the second pattern 72 so that the distribution of the LER of the first pattern 71 and the distribution of the LER of the second pattern 72 have a similar shape, thereby setting the correction values of the luminance of the pixels belonging to the third pattern 73 and the fourth pattern 74.

[0083] For example, when the value of the LER of the third pattern 73 in the captured image G13 is greater than the threshold value in the first parameter set in advance, the determination unit 43a determines that the third pattern 73 has a defect. Further, when the value of the LER of the fourth pattern 74 in the captured image G13 is greater than the threshold value in the second parameter set in advance, the determination unit 43a determines that the fourth pattern 74 has a defect.

[0084] For example, as shown in FIGS. 2 to 4, even when the same mask pattern MP is imaged, the sensitivity may vary depending on the direction on the image plane of the imaged mask pattern MP. Depending on such a difference in sensitivity, for example, the threshold value of the LER as the first parameter for the pattern extending in the first direction and the threshold value of the LER as the second parameter for the pattern extending in the second direction may be different. The threshold value of the edge imaged roughly as shown in FIG. 3 is coarser than the threshold value of the edge imaged smoothly as shown in FIG. 4. By inspecting the sample based on the threshold values preset for each direction in which the pattern extends by the setting unit 42, it is possible to suppress misjudgments such as determining as a defect something that only appears to be a rough edge but is not a defect, and overlooking a defect that appears not to be a defect because it appears to be a smooth edge.

[0085] In the sample 50, when a pattern extending in the first direction and a pattern extending in a second direction different from this by 90° are formed such that their pattern widths and pitch intervals are physically substantially the same, the setting unit 42 sets a first parameter and a second parameter (for example, a threshold value for defect determination) for each direction in which the pattern extends. Thereby, for example, determination considering the difference in resolution due to the difference in NA becomes possible. Further, when the sample 50 is a sample formed such that the physical pattern widths and pitch intervals of a pattern extending in the first direction and a pattern extending in a second direction different from this by 90° are different, and on the imaging image plane, their pattern widths and pitch intervals appear substantially the same, the setting unit 42 sets a first parameter and a second parameter (for example, a threshold value for defect determination) for each direction in which the pattern extends. Thereby, for example, determination considering the difference in resolution due to the difference in the direction of the pattern becomes possible.

[0086] <Image processing method> Next, an image processing method using the image processing apparatus according to the present embodiment will be described. FIG. 14 is a flowchart illustrating an image processing method using the image processing apparatus according to Embodiment 1. As shown in step S11 of FIG. 14, a first parameter and a second parameter are set. Specifically, the setting unit 42 sets a first parameter for the first pattern 71 based on the first sample image region. Further, the setting unit 42 sets a second parameter for the second pattern 72 based on the second sample image region.

[0087] Here, as described above, the setting unit 42 may set the first parameter and the second parameter based on the first sample image region and the second sample image region included in the image obtained by setting the angle formed by the oblique incident illumination on the object having the first pattern to 0° and 90° in the extending direction of the first pattern. The setting unit 42 may also set the first parameter and the second parameter based on the first sample image region and the second sample image region included in the image obtained without changing the angle formed by the oblique incident illumination on the object having the first pattern and the second pattern in the extending direction of the first pattern. Alternatively, the setting unit 42 may set the first parameter and the second parameter based on the first sample image region and the second sample image region generated based on the design data of the object having the first pattern or the object having the first pattern and the second pattern.

[0088] When setting the first parameter, the setting unit 42 may set the first parameter to include a threshold value used for determining the presence or absence of defects in the third pattern included in the captured image G13. Also, when setting the second parameter, the setting unit 42 may set the second parameter to include a threshold value used for determining the presence or absence of defects in the fourth pattern included in the captured image G13.

[0089] Next, as shown in step S12, the captured image G13 is acquired. Specifically, the acquisition unit 41 acquires the captured image G13 obtained by imaging the sample 50a including the third pattern 73 and the fourth pattern 74. The captured image G13 may include both the third pattern 73 and the fourth pattern 74, or may include at least either the third pattern 73 or the fourth pattern 74.

[0090] Next, as shown in step S13, predetermined information processing is performed. Specifically, the processing unit 43 performs predetermined information processing on the captured image G13 based on the first parameter and the second parameter. When performing the predetermined information processing, the processing unit 43 may perform predetermined information processing including determination of the presence or absence of defects in the third pattern 73 and the fourth pattern 74 included in the captured image G13. Alternatively, when performing the predetermined information processing, the processing unit 43 may perform predetermined information processing including image correction of the captured image G13.

[0091] <Inspection method> Next, an inspection method will be described as the operation of the inspection apparatus 1 of the present embodiment. FIG. 16 is a flowchart illustrating an inspection method using the inspection apparatus 1 according to Embodiment 1. As shown in step S101 of FIG. 15, first, the sample 50 is illuminated with the illumination light L11. For example, when illuminating the sample 50 with the illumination light L11 generated by the light source 11, the illumination optical system 10 is arranged so as to achieve critical illumination. Then, the sample 50 is illuminated with the illumination light L11.

[0092] Next, as shown in step S102, the sample 50 is imaged. For example, the imaging optical system 20 images the sample 50 illuminated by the illumination light L11. Then, the imaging optical system 20 outputs a captured image G13 of the sample 50 to the image processing apparatus 40 as a detection result of the detector 23.

[0093] Next, as shown in step S103, the image processing apparatus 40 performs image processing on the captured image G13. Specifically, the image processing apparatus 40 sets the first parameter, the second parameter, etc. as in the above-described image processing method. Then, the image processing apparatus 40 performs predetermined information processing on the captured image acquired from the imaging optical system 20.

[0094] Next, the effects of this embodiment will be described. The image processing apparatus 40 of this embodiment sets a first parameter for the first pattern 71 and a second parameter for the second pattern 72. Thereby, the parameters can be adjusted independently in each of the α-axis direction and the β-axis direction. Therefore, it is possible to appropriately handle the difference in sensitivity caused by the imaging direction of the pattern.

[0095] Also, since the parameters are set in advance for the first pattern 71 and the second pattern 72, it is possible to predict in advance the influence of the difference in resolution in each direction.

[0096] For example, based on the first sample image G11 and the second sample image G12, threshold values for defect determination regarding parameters such as LER, luminance, and line width may be set. Thereby, it is possible to appropriately perform defect determination with respect to the difference in sensitivity caused by the imaging direction of the pattern. For example, since the threshold values used for defect determination of LER in the first pattern 71 and the second pattern 72 are set individually for each of the α-axis direction and the β-axis direction, the influence of LER and the like can be predicted, and the defect detection sensitivity can be optimized.

[0097] As the first sample image G11 and the second sample image G12, actually captured images may be used. Thereby, the accuracy of the parameters can be adapted to the actual captured image G13. Also, the first sample image G11 and the second sample image G12 may be obtained by performing optical simulation with the design pattern of the mask and the NA of the imaging optical system as inputs. Thereby, the labor of actually imaging can be saved, and the parameters can be brought closer to ideal values.

[0098] This embodiment is more effective against differences in appearance due to the illumination direction or the characteristics of the imaging optical system 20, such as oblique incidence illumination where EUV light is incident obliquely. Further, the sample 50 may include an anamorphic mask used by an imaging optical system 20 having different magnifications in the X-axis direction and the Y-axis direction. In a mask for High NA such as an anamorphic mask, the line width in the X-axis direction and the line width in the Y-axis direction may be different. By applying this embodiment to such a sample 50, the defect detection sensitivity can be further optimized. Further, the acquisition unit 41 may acquire an imaging image G13 in which the number of pixels binned in the X-axis direction and the Y-axis direction is different. Since such an imaging image G13 also has a difference in sensitivity due to the imaging direction of the pattern, appropriate measures can be taken by applying this embodiment. It is not necessary for a single device to include all the configurations such as the acquisition unit 41, the setting unit 42, and the processing unit 43. For example, the acquisition unit 41, the setting unit 42, and the processing unit 43 may be separately implemented in two or more devices such as an optical device and a server device, and the image processing device may be configured by causing the respective devices to communicate with each other. Further, the image processing device may be configured to function as the acquisition unit 41, the setting unit 42, and the processing unit 43 by causing two or more devices such as an optical device and a server device to communicate with each other.

[0099] (Embodiment 2) Next, the image processing device 40 according to Embodiment 2 will be described. This embodiment uses image conversion parameters such as a kernel. The image processing device 40 of this embodiment also has the same configuration as the image processing device 40 of Embodiment 1 and includes an acquisition unit 41, a setting unit 42, and a processing unit 43.

[0100] The acquisition unit 41 acquires a sample image that is an imaging image of the sample 50 captured by a predetermined imaging optical system 20.

[0101] The setting unit 42 sets image conversion parameters based on a first sample image region, which is a region including a first pattern extending in a first direction in the reference image plane, and a second sample image region, which is a region including a second pattern extending in a second direction in the reference image plane. Here, the image conversion parameters include, for example, a one-dimensional kernel and a two-dimensional kernel. In the following, as an example of the image conversion parameters, a one-dimensional kernel and a two-dimensional kernel will be used for explanation. Note that the image conversion parameters are not limited to a one-dimensional kernel and a two-dimensional kernel, and may include, for example, the aforementioned first parameter and second parameter. Note that the first sample image region and the second sample image region may be obtained by imaging an object by the acquisition unit 41, or may be obtained by imaging a sample 50.

[0102] FIG. 16 is a diagram illustrating a first pattern extending in a first direction, a luminance distribution along a second direction in the first pattern, and a one-dimensional kernel K11 applied to the luminance distribution in the image processing apparatus 40 according to Embodiment 2. FIG. 17 is a diagram illustrating a second pattern extending in a second direction, a luminance distribution along a first direction in the second pattern, and a one-dimensional kernel K12 applied to the luminance distribution in the image processing apparatus 40 according to Embodiment 2. FIG. 18 is a diagram illustrating a luminance distribution of a reference shape along a direction orthogonal to the direction in which the pattern extends in the image processing apparatus 40 according to Embodiment 2.

[0103] As shown in FIG. 16, the one-dimensional kernel K11 may correspond to a luminance distribution along a second direction in the first pattern extending in the first direction. The luminance distribution along the second direction in the first pattern may be referred to as a first luminance distribution. The one-dimensional kernel K11 may include parameters of vectors or matrix elements arranged in the second direction. The one-dimensional kernel K11 is an image conversion parameter that converts the first luminance distribution shown in FIG. 16 to resemble the luminance distribution of the reference shape shown in FIG. 18.

[0104] For example, the setting unit 42 sets a one-dimensional kernel K11 that includes components of a moving average filter and components of a sharpening filter. Here, the moving average filter is a filter that smooths the luminance distribution. The sharpening filter is a filter that sharpens the luminance distribution. The setting unit 42 sets the parameters of the one-dimensional kernel K11 by adjusting the ratio of the components of the moving average filter and the ratio of the components of the sharpening filter. The setting unit 42 sets the parameters of the one-dimensional kernel K11 so that the first luminance distribution resembles the luminance distribution of the reference shape.

[0105] As shown in FIG. 17, the one-dimensional kernel K12 may correspond to the luminance distribution along the first direction in the second pattern extending in the second direction. The luminance distribution along the first direction in the second pattern may be referred to as the second luminance distribution. The one-dimensional kernel K12 may include parameters of vectors or matrix elements arranged in the first direction. The one-dimensional kernel K12 is an image conversion parameter that converts the second luminance distribution shown in FIG. 17 to resemble the luminance distribution of the reference shape shown in FIG. 18. In this case, the luminance distribution of the reference shape shown in FIG. 18 is rotated 90° so as to be a luminance distribution along the first direction, but in the following description, the explanation of the 90° rotation may be omitted for simplicity.

[0106] For example, the setting unit 42 sets a one-dimensional kernel K12 that includes components of a moving average filter and components of a sharpening filter. The setting unit 42 sets the parameters of the one-dimensional kernel K12 by adjusting the ratio of the components of the moving average filter and the ratio of the components of the sharpening filter. The setting unit 42 sets the parameters of the one-dimensional kernel K12 so that the second luminance distribution resembles the luminance distribution of the reference shape. For example, the setting unit 42 may increase the components of the sharpening filter more than the components of the moving average filter in order to make the second luminance distribution in FIG. 17 resemble the luminance distribution of the reference shape in FIG. 18.

[0107] The luminance distribution of the reference shape shown in FIG. 18 may be the luminance distribution along the direction orthogonal to the direction in which the pattern in the reference image extends, or may be the luminance distribution obtained from optical simulation. Further, the luminance distribution of the reference shape may be the first luminance distribution shown in FIG. 16 or the second luminance distribution shown in FIG. 17.

[0108] Note that the setting unit 42 may set the one-dimensional kernels K11 and K12 without using the luminance distribution of the reference shape. For example, the setting unit 42 may set the one-dimensional kernels K11 and K12 such that the luminance distribution when the one-dimensional kernel K11 is applied to the first luminance distribution shown in FIG. 16 is similar to the luminance distribution when the one-dimensional kernel K12 is applied to the second luminance distribution shown in FIG. 17. In this case, one of the luminance distributions is rotated by 90°.

[0109] For example, the setting unit 42 changes at least one of the parameters of the one-dimensional kernel K11 and the one-dimensional kernel K12 so that the luminance difference between each pixel of the luminance distribution when the one-dimensional kernel K11 is applied to the first luminance distribution shown in FIG. 16 and the luminance distribution when the one-dimensional kernel K12 is applied to the second luminance distribution shown in FIG. 17 is minimized. The setting unit 42 may set the one-dimensional kernels K11 and K12 so as to include the parameters when the luminance difference between each pixel of both is minimized.

[0110] The luminance distribution obtained by applying the one-dimensional kernel K11 set by the setting unit 42 in the exemplified manner above to the luminance distribution along the second direction in the first pattern extending in the first direction and the luminance distribution obtained by applying the one-dimensional kernel K12 to the luminance distribution along the first direction in the second pattern extending in the second direction will be similar in shape to each other.

[0111] Applying the one-dimensional kernels K11 and K12 to the luminance distribution may mean performing convolution processing on the pixels constituting the luminance distribution using the one-dimensional kernels K11 and K12. The convolution processing using the one-dimensional kernels K11 and K12 may be in accordance with the convolution processing in the two-dimensional kernel K21 or the kernel W, etc., which will be described later.

[0112] The setting unit 42 sets a two-dimensional kernel K21 having two-dimensional parameters corresponding to the first direction and the second direction. That is, the setting unit 42 sets the two-dimensional kernel K21 as an image conversion parameter. The setting unit 42 sets the two-dimensional kernel K21 based on the one-dimensional kernel K11 and the one-dimensional kernel K12. Specifically, the setting unit 42 may set the two-dimensional kernel K21 from the product of the vector that is the one-dimensional kernel K11 and the vector that is the one-dimensional kernel K12. That is, when the one-dimensional kernel K12 is a vertical vector (b1, b2, ···, bn) and the one-dimensional kernel K11 is a horizontal vector (a1, a2, ···, an), the two-dimensional kernel K21 may be set by obtaining an n×n matrix by the product of each element. Here, Cij, which is the element at the i-th row and j-th column in the vertical direction of the two-dimensional kernel K21, is bi×aj. Note that the setting unit 42 may set the two-dimensional kernel K21 from the outer product of the one-dimensional kernel K11 and the one-dimensional kernel K12. In addition, as long as the setting unit 42 can set the two-dimensional kernel K21 using the one-dimensional kernel K11 and the one-dimensional kernel K12, the two-dimensional kernel K21 may be set by a calculation method other than the product and the outer product.

[0113] The two-dimensional kernel K21 may have an asymmetric distribution pattern of two-dimensional parameters in the first direction and the second direction. Such a two-dimensional kernel K21 can be, for example, a kernel set considering the difference in sensitivity in the vertical direction and the horizontal direction. That is, depending on the optical device, the sensitivity may be different in the first direction and the second direction. Therefore, in order to mitigate the difference between the sensitivity in the first direction and the sensitivity in the second direction, the setting unit 42 sets the kernel K21 in which the distribution pattern of the parameters is asymmetric in the first direction and the second direction. Thus, the distribution pattern of the parameters in the two-dimensional kernel K21 is asymmetric in the first direction and the second direction. The two-dimensional kernel K21 is an example of a kernel set considering the difference in sensitivity in the vertical direction and the horizontal direction. In other words, the two-dimensional kernel K21 is an example of a kernel set set to mitigate the difference in sensitivity in the vertical direction and the horizontal direction.

[0114] The processing unit 43 performs predetermined information processing for applying image conversion parameters such as the two-dimensional kernel K21 to the sample image or the image based on the sample image. The two-dimensional kernel K21 may be simply referred to as the kernel W. As described above, the processing unit 43 performs predetermined information processing for applying the kernel W in order to mitigate the difference in the mode of the images captured with different sensitivities in the first direction and the second direction.

[0115] Hereinafter, as the predetermined information processing, <processing of multiplying a kernel to a sample image> will be described. Thereafter, <defect inspection> will be described. Also, in <Modification 1 of Embodiment 2>, <parameters of a kernel based on a difference image> will be described. Thereafter, as the predetermined processing, <processing of multiplying a kernel to a sample image> will be described. Further, in <Modification 2 of Embodiment 2>, as the predetermined information processing, <processing of multiplying a kernel to a difference image> will be described, and <defect inspection> will be described. Furthermore, in <Modification 3 of Embodiment 2>, as the predetermined information processing, processing using a corrected sample image and a corrected difference image will be described. Note that the image based on the sample image includes a difference image, a corrected sample image, and a corrected difference image.

[0116] <Processing of multiplying a kernel to a sample image> As a predetermined information process, the processing unit 43 causes a kernel W having a distribution pattern of parameters set by the setting unit 42 to be applied to a sample image, and outputs a corrected sample image. The kernel W applied to the sample image may be referred to as a first kernel W.

[0117] FIG. 19 is a schematic diagram illustrating information processing performed by the processing unit 43 on a sample image or an image based on the sample image in the image processing apparatus 40 according to the second embodiment. As shown in FIG. 19, the processing unit 43 may perform predetermined information processing for applying the kernel W to the sample image.

[0118] When the reference image plane is placed in the sample image, the sample image is an image formed by a plurality of pixel columns arranged in the first direction and a plurality of pixel columns arranged in the second direction. Here, the sample image is assumed to be an image in which M pixels p are arranged in the first direction and N pixels p are arranged in the second direction.

[0119] The first kernel W having two-dimensional parameters set by the setting unit 42 is, for example, a kernel having 3 rows and 3 columns, that is, 3×3 = 9 cells. The size of each element (which may be referred to as a cell) of the first kernel W may virtually correspond to the size of the pixel p of the sample image.

[0120] The predetermined information process may be, for example, a convolution process described in Non-Patent Document 1. That is, the processing unit 43 may perform a convolution process for applying the first kernel W to the sample image. Specifically, at the pixel p corresponding to the center of the first kernel W, a convolution process is performed between the surrounding 3×3 pixel values (for example, luminance) and the parameters of the first kernel W to filter each pixel in the sample image. For example, each cell of the first kernel W is represented by (i, j) using a local coordinate axis including the x-axis and the y-axis. When a local operator J(p) for performing image filtering is defined in the vicinity of 3×3 of each pixel p, J(p) can be defined as a convolution between the luminance value I(x + i, y + j) around the pixel p = (x, y) on the sample image and W’(p) as shown in the following formula (1) (the convolution is a two-dimensional discrete approximation value).

[0121]

Number

[0122] Here, W’(p) is the kernel obtained by inverting the original first kernel W(p) with respect to both the x-axis and y-axis of the local coordinate axes. Also, w’ i、j is the weight coefficient at each position (i, j) of the inverted kernel W’(p), S>0 is the coefficient for normalization and scaling. When i and j exceed the boundary range of the sample image, padding processing may be performed first, and the pixel value I(x + i, y + j) filled with values around may be used. In this way, the processing unit 43 performs convolution processing on each pixel of the sample image and outputs the processed pixel value. The processing unit 43 can sweep the entire sample image with the first kernel W by sequentially changing the pixel of the sample image where the central cell of the first kernel W is arranged. Thereby, the processing unit 43 acquires a corrected sample image to which the first kernel W is applied for the entire sample image.

[0123] The corrected sample image is an image in which M pixels are arranged in the first direction and N pixels are arranged in the second direction, similar to the sample image. The luminance I’ m、n at each pixel (p’ m、n ) of the corrected sample image is changed from the luminance I m、n of each pixel (p m、n ) of the sample image by the application of the first kernel W. The corrected sample image is an image output by applying the first kernel W having different parameter distributions in the first direction and the second direction to the sample image. Therefore, the corrected sample image is an image in which the difference in sensitivity in the first direction and the second direction is alleviated compared to the sample image.

[0124] <Defect inspection> The processing unit 43 detects a defect based on the difference image between the reference image and the corrected sample image. The reference image may be a good product image representing an image without abnormalities or an image without critical abnormalities. The difference image may include, as a parameter for a pixel, the difference in luminance of pixels having the same relative position among the pixels of the reference image and the pixels of the corrected sample image. The difference image may also include, as a parameter for a pixel, the ratio of the luminance of pixels having the same relative position among the pixels of the reference image and the pixels of the corrected sample image. Hereinafter, the parameter of the pixel of the difference image will simply be referred to as luminance. The processing unit 43 may detect a defect based on whether the luminance of the pixels included in the difference image exceeds a predetermined threshold value.

[0125] <Modification Example 1 of Embodiment 2> <Parameter Setting of Kernel Based on Difference Image> The setting unit 42 may set image conversion parameters based on an image based on a comparison between the captured image of the object and the reference image of the captured image, or an image based on a comparison between the sample image, which is the captured image of the sample, and the reference image of the sample image.

[0126] Hereinafter, it will be described that the setting unit 42 sets image conversion parameters based on an image based on a comparison between the captured image of the object and the reference image of the captured image. The image based on a comparison between the captured image of the object and the reference image of the captured image is, for example, the difference image between the captured image and the reference image. The reference image may be a good product image representing an image without abnormalities or an image without critical abnormalities. The difference image may include, as a parameter for a pixel, the difference in luminance of pixels having the same relative position among the pixels of the reference image and the pixels of the captured image of the object. The difference image may also include, as a parameter for a pixel, the ratio of the luminance of pixels having the same relative position among the pixels of the reference image and the pixels of the captured image. Hereinafter, the parameter of the pixel of the difference image will simply be referred to as luminance.

[0127] As will be described below, in Modification 1 of Embodiment 2, it is not essential that the object or sample 50 has a pattern extending in one direction. In other words, the object or sample 50 may not have a pattern extending in one direction. Due to the recent complexity of semiconductor structures, samples 50 such as photomasks and wafers may have patterns extending in one direction, patterns extending in a direction perpendicular to one direction, as well as various shaped patterns such as curved patterns, obliquely extending patterns, and contact holes. Here, according to Modification 1 of Embodiment 2, regardless of the shape and type of the pattern formed on the object or sample 50, the setting unit 42 can set image conversion parameters in consideration of the difference in NA and sensitivity between the vertical direction and the horizontal direction.

[0128] FIG. 20 is a diagram illustrating a difference image in the image processing apparatus 40 according to Modification 1 of Embodiment 2. The difference image (a) in FIG. 20 shows the luminance distribution along the first direction, and the difference image (b) shows the luminance distribution along the second direction. As shown in FIG. 20, the setting unit 42 sets the one-dimensional kernel K12 in the difference image (a) between the captured image when the relative orientation between the object and the imaging optical system is the predetermined orientation and the reference image of the captured image. A region having a luminance exceeding a predetermined threshold is called a defect region. The luminance distribution when the one-dimensional kernel K12 is applied to the luminance distribution along the first direction when the plane of the difference image (a) including the defect region is the reference image plane is called the third luminance distribution. The imaging optical system has different NAs in the first direction when its captured image is the reference image plane and in the second direction orthogonal to the first direction. The imaging optical system may alternatively or in addition have different imaging magnifications in the first direction when its captured image is the reference image plane and in the second direction orthogonal to the first direction.

[0129] The setting unit 42 sets the one-dimensional kernel K11 in the difference image (b) between the captured image when the relative orientation between the object and the imaging optical system is an orientation different from the predetermined orientation by 90° and the reference image of the captured image. A region corresponding to the defective region in the difference image (b) is called a rotational defective region. The luminance distribution when the one-dimensional kernel K11 is applied to the luminance distribution along the second direction when the plane of the difference image (b) including the rotational defective region is used as the reference image plane is called the fourth luminance distribution. Note that the second direction is, for example, a direction different from the first direction by 90°.

[0130] The setting unit 42 sets the one-dimensional kernel K11 and the one-dimensional kernel K12 so that the third luminance distribution and the fourth luminance distribution are similar to each other.

[0131] In this way, the setting unit 42, in the difference image between the captured image when the relative orientation between the object and the imaging optical system is the predetermined orientation and the reference image of the captured image, for the luminance distribution along the first direction when the one-dimensional kernel K12 is applied to the region having a luminance exceeding a predetermined threshold (hereinafter referred to as the defective region) in the difference image (hereinafter referred to as the defective region), and the captured image when the relative orientation between the object and the imaging optical system is an orientation different from the predetermined orientation by 90°, and the reference image of the captured image, the luminance distribution when the one-dimensional kernel K11 is applied to the luminance distribution along the second direction different from the first direction by 90° of the rotational defective region, which is the region corresponding to the defective region in the difference image, are similar to each other, and sets the one-dimensional kernel K11 and the one-dimensional kernel K12. The defective region may be appropriately referred to as the region of interest.

[0132] Here, the differences in the luminance distributions of the defect regions in the first direction and the second direction in the differential images (a) and (b) may occur due to differences in NA in the vertical and horizontal directions, differences in magnification and sensitivity, and the shape of the defect region (being vertically long in the α direction in FIG. 20). Therefore, the setting unit 42 sets the image conversion parameters based on the luminance distributions in the first direction and the second direction between the defect regions in the differential images where the relative orientations of the object and the imaging optical system differ by 90° from each other. Thereby, the difference in the luminance distribution caused by the shape of the defect region can be minimized, and appropriate image conversion parameters can be set.

[0133] The setting unit 42 may set the one-dimensional kernel K11 and the one-dimensional kernel K12 such that the luminance distribution when the one-dimensional kernel K12 is applied to the luminance distribution along the first direction of the defect region and the luminance distribution when the one-dimensional kernel K11 is applied to the luminance distribution along the second direction of the rotated defect region both resemble the luminance distribution of the reference shape. Also, the setting unit 42 may set the one-dimensional kernel K11 and the one-dimensional kernel K12 without using the luminance distribution of the reference shape. For example, the one-dimensional kernel K11 and the one-dimensional kernel K12 may be set such that one resembles the luminance distribution of the other. Alternatively, the setting unit 42 may change at least one of the parameters of the one-dimensional kernel K11 and the one-dimensional kernel K12 so that the luminance difference between each pixel in the luminance distributions of both when the one-dimensional kernels corresponding to the luminance distributions of both are applied becomes minimum, thereby setting the one-dimensional kernel K11 and the one-dimensional kernel K12.

[0134] The setting unit 42 may set the two-dimensional kernel K21 based on the one-dimensional kernel K11 and the one-dimensional kernel K12. Specifically, the setting unit 42 may set the two-dimensional kernel K21 from the product of the vector that is the one-dimensional kernel K11 and the vector that is the one-dimensional kernel K12. Note that the setting unit 42 may set the two-dimensional kernel K21 from the outer product of the one-dimensional kernel K11 and the one-dimensional kernel K12. In addition, as long as the setting unit 42 can set the two-dimensional kernel K21 using the one-dimensional kernel K11 and the one-dimensional kernel K12, the two-dimensional kernel K21 may be set by a calculation method other than the product or the outer product.

[0135] In the setting unit 42, in this way, the two-dimensional kernel K21 set based on the difference image is also a kernel set in consideration of the difference in NA, magnification, and sensitivity in the vertical and horizontal directions. In other words, it can be said to be an example of a kernel set to mitigate the difference in NA, magnification, and sensitivity in the vertical and horizontal directions.

[0136] <Processing of multiplying a kernel by a sample image> As a predetermined information process, the processing unit 43 applies a kernel W having a distribution pattern of parameters set by the setting unit 42 to a sample image and outputs a corrected sample image. That is, the processing unit 43 may apply the two-dimensional kernel K21, which is an image conversion parameter set based on an image based on the comparison between the captured image of the object and the reference image of the captured image, to the sample image by the setting unit 42 and output a corrected sample image. Since the two-dimensional kernel K21 at this time is the kernel W to be applied to the sample image, it is an example of the first kernel W.

[0137] As described above, the sample 50, which is the object for performing predetermined information processing such as determination of the presence or absence of defects, and the object may be the same object or different objects.

[0138] Also, in this Modification Example 1, the object or sample 50 does not necessarily have a pattern formed extending in one direction. In this Modification Example 1, image conversion parameters are set based on the defect region in the difference image. Here, the defect region in the difference image can occur regardless of the shape and type of the pattern.

[0139] <Modification Example 2 of Embodiment 2> <Process of applying a kernel to the difference image> The processing unit 43 may output a corrected difference image by applying a kernel having a distribution of parameters set by the setting unit 42 to the difference image as a predetermined information process. The reference image may be a non-abnormal image or a non-defective image representing an image without critical abnormalities. The difference image may include, as parameters for a pixel, the difference in luminance of pixels having the same relative position among the pixels of the reference image and the pixels of the corrected sample image. The difference image may include, as parameters for a pixel, the ratio of the luminance of pixels having the same relative position among the pixels of the reference image and the pixels of the corrected sample image. Alternatively, the difference image may include, as parameters for a pixel, the difference in luminance of pixels having the same relative position among the pixels of the reference image and the sample image. The difference image may include, as parameters for a pixel, the ratio of the luminance of pixels having the same relative position among the pixels of the reference image and the sample image.

[0140] Here, the kernel to be applied to the difference image may be a kernel set by the setting unit 42 based on a first sample image region that is a region including a first pattern extending in a first direction in the reference image plane and a second sample image region that is a region including a second pattern extending in a second direction orthogonal to the first direction in the reference image plane, as shown in Embodiment 2. Alternatively, the kernel to be applied to the difference image may be a kernel set by the setting unit 42 based on an image based on a comparison between a captured image of an object (or sample) and a reference image of the captured image, as shown in Modification Example 1 of Embodiment 2. In this case, the object or sample 50 does not have to have a pattern extending in one direction. The kernel to be applied to the difference image may be referred to as the second kernel W2.

[0141] When the reference image plane is placed in the difference image, the difference image may be an image composed of a plurality of pixel columns arranged in the first direction and a plurality of pixel columns arranged in the second direction. Here, assume that the difference image is an image in which M pixels are arranged in the first direction and N pixels are arranged in the second direction. Then, the size of each cell of the second kernel W2 virtually corresponds to the size of the pixels of the difference image. Then, for the entire sample image described above, in the same process as when the first kernel W is applied, the processing unit 43 can obtain a corrected difference image by applying the second kernel W2 to the entire difference image.

[0142] Similar to the difference image, the corrected difference image is an image in which M pixels are arranged in the first direction and N pixels are arranged in the second direction. The luminance I''' m、n at each pixel (p''') m、n of the corrected difference image has been changed from the luminance I'' m、n of each pixel (p'') m、n of the difference image by the application of the second kernel W2. The corrected difference image is an image output by applying the second kernel W2 having different parameter distributions in the first direction and the second direction to the difference image. Therefore, the corrected difference image is an image in which the difference in sensitivity in the first direction and the second direction is alleviated compared to the difference image.

[0143] <Defect inspection> The processing unit 43 detects a defect based on the corrected difference image. The processing unit 43 may detect a defect based on whether the luminance of the pixels included in the corrected difference image exceeds a predetermined threshold value.

[0144] <Modification Example 3 of Embodiment 2> As a predetermined information process, the processing unit 43 may acquire a corrected sample image obtained by applying a first kernel W to a sample image, and acquire a corrected difference image obtained by applying a second kernel W2 to a difference image between the reference image (which may be a non-defective image corresponding to the sample image or an image obtained by applying the first kernel W to the non-defective image) and the corrected sample image. Then, the processing unit 43 may detect a defect based on the corrected difference image.

[0145] Here, when a specific defect image is included in the difference image between the corrected sample image and the reference image, the processing unit 43 may acquire a corrected difference image obtained by applying the second kernel W2 to the difference image. That is, when a specific defect image is included in the difference image between the corrected sample image and the reference image, the processing unit 43 evaluates the sample 50 based on the corrected difference image obtained by applying the second kernel W2 to the difference image, while when a specific defect image is not included in the difference image between the corrected sample image and the reference image, the processing unit 43 may evaluate the sample 50 based on the difference image. The case where a specific defect image is included may include, for example, the case where pixels having a luminance exceeding a predetermined threshold value exist over a plurality of predetermined regions in the difference image.

[0146] Here, the setting unit 42 may be the same for the first kernel W and the second kernel W2. The setting unit 42 may make the first kernel W and the second kernel W2 different. For the first kernel W, as described above, the setting unit 42 may set the first kernel W to have a parameter distribution that is asymmetric in the first direction and the second direction based on a first sample image region, which is a region including a first pattern extending in the first direction in the reference image plane, and a second sample image region, which is a region including a second pattern extending in a second direction orthogonal to the first direction in the reference image plane (Embodiment 2). Alternatively, the setting unit 42 may set the first kernel W to have a parameter distribution that is asymmetric in the first direction and the second direction based on a defect region in a difference image between a captured image of an object (or sample 50) and a reference image (Modification Example 1 of Embodiment 2). On the other hand, for the second kernel W2, as will be described later, the setting unit 42 may set it by a method based on a different idea or purpose from the above. That is, the first kernel W is a kernel set in consideration of the difference in sensitivity in the vertical and horizontal directions, while the second kernel W2 may be a kernel set for a different effect.

[0147] For example, the setting unit 42 may set the parameters of the second kernel W2 as follows based on the transferability of defects in the sample. That is, the second kernel W2 may be set in consideration of the transferability during the exposure of foreign matters such as defects.

[0148] <Method for Setting the Second Kernel> For example, prepare a sample image and an image of a substrate such as a wafer on which a sample is pattern-formed using a patterning device (referred to as a substrate image). Then, the setting unit 42 sets the parameters of the kernel W so that the converted sample image obtained by applying the kernel W to the sample image resembles the substrate image. Note that when setting the parameters of the kernel W, the setting unit 42 may set the parameters of the kernel W based on a learning model obtained by learning a plurality of pairs of sample images and substrate images as learning data. Alternatively, the setting unit 42 may use optical simulation to derive a substrate image from the sample image in advance and set a kernel W that can obtain equivalent results. The setting unit 42 may set the parameters of the second kernel W2 to be applied to the difference image based on the parameters of the kernel W derived from the sample image in the manner exemplified above. Such a kernel can be said to be an example of a kernel set in consideration of the transferability during the exposure of foreign matter.

[0149] <Predetermined information processing> As a predetermined information process, the processing unit 43 may obtain a corrected sample image obtained by applying the first kernel W1 to the sample image, and obtain a corrected difference image obtained by applying the second kernel W2 to the difference image between the reference image and the corrected sample image. Then, the processing unit 43 may detect a defect based on the corrected difference image. Here, as described above, the first kernel W is a kernel set in consideration of the difference in sensitivity in the vertical and horizontal directions. Also, as described above, the second kernel W is the second kernel W2 set in consideration of the transferability during the exposure of foreign matter.

[0150] In this way, when analyzing the sample image, by applying together the kernel (first kernel W) set in consideration of the difference in sensitivity in the vertical and horizontal directions and the kernel (second kernel W2) set in consideration of the transferability during the exposure of foreign matter to the sample image, an appropriate inspection considering the difference in sensitivity in the vertical and horizontal directions and the transferability during the exposure of foreign matter can be realized.

[0151] In the above description, the first kernel W applied to the sample image is set as a kernel that takes into account the difference in sensitivity in the vertical and horizontal directions, and the second kernel W2 applied to the difference image is set as a kernel that takes into account the transferability during the exposure of foreign matter. However, the present invention is not limited to this. The second kernel W2 applied to the reference image may be set as a kernel that takes into account the difference in sensitivity in the vertical and horizontal directions, and the first kernel W applied to the sample image may be set as a kernel that takes into account the transferability during the exposure of foreign matter.

[0152] FIG. 21 is a flowchart illustrating an image processing method using the image processing apparatus 40 according to Embodiment 2. As shown in FIG. 21, the image processing method of the present embodiment includes a step S21 of setting image conversion parameters, a step S22 of acquiring an image, and a step S23 of performing predetermined information processing. Note that steps S21 and S22 may be performed in reverse order or in parallel.

[0153] In step S21, the setting unit 42 sets the image conversion parameters based on a first sample image region that is a region including a first pattern extending in a first direction in the reference image plane and a second sample image region that is a region including a second pattern extending in a second direction orthogonal to the first direction in the reference image plane. The image conversion parameters may include a kernel having two-dimensional parameters corresponding to the first direction and the second direction, and the distribution pattern of the parameters may be asymmetric between the first direction and the second direction. Note that in step S21, the setting unit 42 may set the image conversion parameters based on the transferability of the defect of the sample.

[0154] Further, the setting unit 42 is based on the luminance distribution along the first direction of the attention area in the image based on the comparison between the captured image of the object when the relative orientation between the object and the predetermined imaging optical system is the predetermined orientation and the reference image corresponding to the captured image, with the plane of the image based on this comparison as the reference image plane, and the luminance distribution along the second direction of the rotation attention area, which is the area corresponding to the attention area in the image based on the comparison between the captured image of the object when the relative orientation between the object and the predetermined imaging optical system is an orientation approximately 90° different from the predetermined orientation and the reference image corresponding to the captured image, with the plane of the image based on this comparison as the reference image plane. Based on these, the image conversion parameters may be set.

[0155] In step S22, the acquisition unit 41 acquires an image. The acquisition unit 41 acquires, for example, a sample image that is a captured image of a sample by a predetermined imaging optical system. The acquisition unit 41 may acquire a captured image of an object by a predetermined imaging optical system in which the NA is different in the first direction and the second direction orthogonal to the first direction in the reference image plane. The acquisition unit 41 may acquire a captured image of an object by a predetermined imaging optical system in which the imaging magnification is different in the first direction and the second direction orthogonal to the first direction in the reference image plane.

[0156] In step S23, the processing unit 43 performs predetermined information processing for applying image conversion parameters to the sample image or an image based on the sample image. The predetermined information processing may be processing for applying a kernel to the sample image or processing for applying a kernel to the difference image. Further, the predetermined information processing may be the above-described processing using the corrected sample image and the corrected difference image.

[0157] As described above, the embodiments of the present disclosure have been described. However, the present disclosure includes appropriate modifications that do not impair its purpose and advantages, and is not further limited by the above embodiments. Also, combinations and omissions of each configuration of Embodiment 1 as appropriate are also within the scope of the technical idea of the present disclosure. Further, the following configurations are also within the scope of the technical idea of the embodiment.

[0158] (Appendix 1) Based on a first sample image region, which is a region including a first pattern extending in a first direction in a reference image plane, a step of setting a first parameter for the first pattern; Based on a second sample image region, which is a region including a second pattern extending in a second direction orthogonal to the first direction in the reference image plane, a step of setting a second parameter for the second pattern; A step of acquiring a sample image, which is an image obtained by imaging a sample having a third pattern extending in the first direction and a fourth pattern extending in the second direction in the imaging image when the plane of the imaging image is the reference image plane, by a predetermined imaging optical system; A step of performing predetermined information processing on the sample image based on the first parameter and the second parameter; An image processing method comprising the above. (Appendix 2) In the step of setting the first parameter, Set the first parameter to include a threshold value used for determining the presence or absence of a defect in the third pattern included in the sample image; In the step of setting the second parameter, Set the second parameter to include a threshold value used for determining the presence or absence of a defect in the fourth pattern included in the sample image; In the step of performing the predetermined information processing, Perform the predetermined information processing including determining the presence or absence of a defect in the third pattern and the fourth pattern included in the sample image; The image processing method according to Appendix 1. (Appendix 3) The sample image includes both the third pattern and the fourth pattern; In the step of performing the predetermined information processing, Perform the predetermined information processing including determining the presence or absence of a defect in the third pattern and the fourth pattern included in the sample image; The image processing method according to Appendix 2. (Appendix 4) In the step of setting the first parameter and the step of setting the second parameter, the threshold value is set for a plurality of types of physical quantities regarding the information of the sample image, The image processing method according to Supplementary Note 2. (Supplementary Note 5) In the step of setting the first parameter and the step of setting the second parameter, at least one of the type and the number of the physical quantities for which the threshold value is defined as the first parameter is set to be different from the physical quantity for which the threshold value is defined as the second parameter, The image processing method according to Supplementary Note 4. (Supplementary Note 6) further comprising the step of acquiring the first sample image region and the second sample image region, In the step of acquiring the first sample image region and the second sample image region, at least one of the first sample image region and the second sample image region is a region included in an image generated based on the design data of the sample or the design data of a pattern formed on the sample, The image processing method according to Supplementary Note 1. (Supplementary Note 7) The first sample image region is a region included in an imaging image of an object having the first pattern by the predetermined imaging optical system, The image processing method according to Supplementary Note 1. (Supplementary Note 8) The first sample image region and the second sample image region are regions included in an imaging image of an object having the first pattern and the second pattern by the predetermined imaging optical system, The image processing method according to Supplementary Note 7. (Supplementary Note 9) The first sample image region and the second sample image region are regions included in an imaging image of an object having the first pattern by the predetermined imaging optical system, The orientation of the object with respect to the predetermined imaging optical system at the time of imaging the captured image including the first sample image region and the orientation of the object with respect to the predetermined imaging optical system at the time of imaging the captured image including the second sample image region are different by 90° in the principal plane of the object. The image processing method according to Supplementary Note 7. (Supplementary Note 10) The predetermined imaging optical system captures an image by oblique incident illumination on the object. The first sample image region is included in the captured image when the angle formed by the direction in which the main axis of the oblique incident illumination is projected onto the upper surface of the object and the first direction is a predetermined angle. The image processing method according to Supplementary Note 7. (Supplementary Note 11) The predetermined imaging optical system captures an image by oblique incident illumination on the object. The first sample image region and the second sample image region are included in the captured image when the angle formed by the direction in which the main axis of the oblique incident illumination is projected onto the upper surface of the object and the first direction is a predetermined angle. The image processing method according to Supplementary Note 9. (Supplementary Note 12) The predetermined imaging optical system captures an image by oblique incident illumination on the sample. The sample image is a captured image by the predetermined imaging optical system when the angle formed by the direction in which the main axis of the oblique incident illumination is projected onto the upper surface of the sample and the first direction is a predetermined angle. The image processing method according to Supplementary Note 1. (Supplementary Note 13) The sample includes an anamorphic mask. The image processing method according to Supplementary Note 12. (Supplementary Note 14) In the step of obtaining the captured image, A sample image in which the number of pixels binned in the first direction and the second direction is different is obtained. The image processing method according to Supplementary Note 1. (Supplementary Note 15) In the step of obtaining the captured image, Obtaining the captured image captured by an imaging optical system in which NA is different in the first direction and the second direction The image processing method according to Supplementary Note 1 (Supplementary Note 16) In the step of setting the first parameter Setting the first parameter to include a correction value of the luminance of pixels belonging to the third pattern included in the sample image In the step of setting the second parameter Setting the second parameter to include a correction value of the luminance of pixels belonging to the fourth pattern included in the sample image In the step of performing the predetermined information processing Performing the predetermined information processing including image correction of the sample image The image processing method according to Supplementary Note 1 (Supplementary Note 17) The step of illuminating the sample The step of imaging the illuminated sample The image processing method according to any one of Supplementary Notes 1 to 16 A method of using an optical device including the same

Explanation of Signs

[0159] 1 Inspection apparatus 10 Illumination optical system 11 Light source 12 Elliptical mirror 13 Elliptical mirror 14 Condensing mirror 20 Imaging optical system 21 Concave mirror with a hole 21a Hole 22 Convex mirror 23 Detector 40 Image processing apparatus 41 Acquisition unit 42 Setting unit 43 Processing unit 43a Determination unit 43b Image correction unit 50, 50a, 50b Sample 51 Upper surface 52 Stages 71 First Pattern 72 Second Pattern 73 Third Pattern 74 Fourth Pattern G01, G02 Images G11 First Sample Image G12 Second Sample Image G13 Captured Image IF1 Focus Point K11, K12 One - Dimensional Kernel K21 Two - Dimensional Kernel L11 Illumination Light L12 Reflected Light MP, MP1, MP2 Mask Patterns W First Kernel W2 Second Kernel

Claims

1. setting first parameters for the first pattern based on a first sample image region, the first sample image region being a region including a first pattern extending in a first direction in a reference image plane; a setting unit that sets a second parameter for the second pattern based on a second sample image area that is an area including a second pattern extending in a second direction perpendicular to the first direction in the reference image plane; an acquisition unit that acquires a sample image, which is an image obtained by imaging a sample having a third pattern extending in the first direction and a fourth pattern extending in the second direction in the image when a plane of the image is defined as the reference image plane, using a predetermined imaging optical system; a processing unit that performs a predetermined information processing on the sample image based on the first parameter and the second parameter; An image processing device comprising:

2. The setting unit is The first parameter is set to include a threshold value used to determine the presence or absence of a defect in the third pattern included in the sample image; The second parameter is set to include a threshold value used to determine the presence or absence of the defect in the fourth pattern included in the sample image; the processing unit performs the predetermined information processing including determining the presence or absence of the defect in the third pattern and the fourth pattern included in the sample image. The image processing device according to claim 1 .

3. the sample image includes both the third pattern and the fourth pattern, the processing unit performs the predetermined information processing including determining the presence or absence of the defect in the third pattern and the fourth pattern included in the sample image. The image processing device according to claim 2 .

4. The setting unit sets the threshold values ​​for a plurality of types of physical quantities of the information of the sample image. The image processing device according to claim 2 .

5. the setting unit sets at least one of the type of the physical quantity and the number of the physical quantities for which the threshold is determined as the first parameter so as to be different from the physical quantity for which the threshold is determined as the second parameter. The image processing device according to claim 4.

6. At least one of the first sample image area and the second sample image area is an area included in an image generated based on design data of the sample or design data of a pattern formed on the sample. The image processing device according to claim 1 .

7. The first sample image area is an area included in the captured image of the object having the first pattern by the predetermined imaging optical system. The image processing device according to claim 1 .

8. the first sample image area and the second sample image area are areas included in the captured image of an object having the first pattern and the second pattern by the predetermined imaging optical system; The image processing device according to claim 7.

9. the first sample image area and the second sample image area are areas included in the captured image of the object having the first pattern by the predetermined imaging optical system, a direction of the object relative to the predetermined imaging optical system when the captured image including the first sample image area is captured and a direction of the object relative to the predetermined imaging optical system when the captured image including the second sample image area is captured differ by 90° on a principal plane of the object; The image processing device according to claim 7.

10. The predetermined imaging optical system captures an image of the object by oblique incidence illumination, the first sample image area is included in the captured image when an angle formed between a direction in which a principal axis of the oblique incidence illumination is projected onto an upper surface of the object and the first direction is a predetermined angle; The image processing device according to claim 7.

11. The predetermined imaging optical system captures an image of the object by oblique incidence illumination, the first sample image area and the second sample image area are included in the captured image when an angle formed between a direction in which a principal axis of the oblique incidence illumination is projected onto an upper surface of the object and the first direction is a predetermined angle. The image processing device according to claim 8.

12. The predetermined imaging optical system captures an image of the sample by oblique incidence illumination, the sample image is an image captured by the predetermined imaging optical system when an angle formed between a direction in which a principal axis of the oblique incidence illumination is projected onto an upper surface of the sample and the first direction is a predetermined angle. The image processing device according to claim 1 .

13. The sample includes an anamorphic mask. The image processing device according to claim 12.

14. the acquisition unit acquires the sample image in which the number of pixels to be binned in the first direction differs from the number of pixels to be binned in the second direction. The image processing device according to claim 1 .

15. The predetermined imaging optical system has a different NA in the first direction and in the second direction. The image processing device according to claim 1 .

16. The setting unit is The first parameter is set to include a correction value for the luminance of a pixel belonging to the third pattern included in the sample image; The second parameter is set to include a correction value for the luminance of a pixel belonging to the fourth pattern included in the sample image; The processing unit performs the predetermined information processing including image correction of the sample image. The image processing device according to claim 1 .

17. a setting unit that sets image conversion parameters based on a first sample image area, the first sample image area being an area including a first pattern extending in a first direction on a reference image plane, and a second sample image area, the second sample image area being an area including a second pattern extending in a second direction perpendicular to the first direction on the reference image plane; an acquisition unit that acquires a sample image, which is an image of the sample captured by a predetermined imaging optical system; a processing unit that performs a predetermined information processing for applying the image conversion parameters to the sample image or an image based on the sample image; An image processing device comprising:

18. an acquisition unit that acquires an image of an object captured by a predetermined imaging optical system having a different NA in a first direction and a second direction perpendicular to the first direction in a reference image plane; a setting unit that sets image conversion parameters based on a luminance distribution along the first direction of a region of interest in an image based on a comparison between a captured image of the object and a reference image corresponding to the captured image when a relative orientation between the object and the specified imaging optical system is a specified orientation, the plane of the image based on the comparison being the reference image plane, and a luminance distribution along the second direction of a rotational region of interest, which is a region corresponding to the region of interest in an image based on a comparison between a captured image of the object and a reference image corresponding to the captured image when a relative orientation between the object and the specified imaging optical system is an orientation different by approximately 90° from the specified orientation, the plane of the image based on the comparison being the reference image plane; a processing unit that performs a predetermined information processing to apply the image conversion parameters to a sample image, which is an image of a sample captured by the predetermined imaging optical system, or an image based on the sample image; An image processing device comprising:

19. the image transformation parameters include a kernel having two-dimensional parameters corresponding to the first direction and the second direction, the kernel having a distribution pattern of the parameters being asymmetric between the first direction and the second direction; 19. The image processing device according to claim 17 or 18.

20. an illumination optical system for illuminating the sample; the predetermined imaging optical system for imaging the illuminated sample; An image processing device according to any one of claims 1 to 18, An optical device comprising:

21. setting first parameters for the first pattern based on a first sample image area, the first sample image area being an area including a first pattern extending in a first direction in a reference image plane; setting second parameters for the second pattern based on a second sample image area that is an area including a second pattern extending in a second direction perpendicular to the first direction in the reference image plane; acquiring a sample image, the sample having a third pattern extending in the first direction and a fourth pattern extending in the second direction in the captured image when a plane of the captured image is defined as the reference image plane, by using a predetermined imaging optical system; performing a predetermined information processing on the sample image based on the first parameter and the second parameter; An image processing method comprising:

22. setting image conversion parameters based on a first sample image area, the first sample image area being an area including a first pattern extending in a first direction in a reference image plane, and a second sample image area, the second sample image area being an area including a second pattern extending in a second direction perpendicular to the first direction in the reference image plane; acquiring a sample image, which is an image of the sample captured by a predetermined imaging optical system; performing a predetermined information processing step of applying the image transformation parameters to the sample image or an image based on the sample image; An image processing method comprising:

23. acquiring an image of an object captured by a predetermined imaging optical system having a different NA in a first direction and a second direction perpendicular to the first direction in a reference image plane; setting an image conversion parameter based on a luminance distribution along the first direction of a region of interest in an image based on a comparison between a captured image of the object and a reference image corresponding to the captured image when a relative orientation between the object and the specified imaging optical system is a specified orientation, the plane of the image based on the comparison being the reference image plane, and a luminance distribution along the second direction of a rotational region of interest, which is a region corresponding to the region of interest in an image based on a comparison between a captured image of the object and a reference image corresponding to the captured image when a relative orientation between the object and the specified imaging optical system is an orientation different by approximately 90° from the specified orientation, the plane of the image based on the comparison being the reference image plane; performing a predetermined information processing step of applying the image transformation parameters to a sample image, which is an image of a sample captured by the predetermined imaging optical system, or an image based on the sample image; An image processing method comprising:

24. the image transformation parameters include a kernel having two-dimensional parameters corresponding to the first direction and the second direction, the kernel having a distribution pattern of the parameters being asymmetric between the first direction and the second direction; 24. The image processing method according to claim 22 or 23.

25. Illuminating the sample; imaging the illuminated sample; An image processing method according to any one of claims 21 to 23, A method for using an optical device comprising the steps of:

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