JP2000270349A - Color unevenness defect inspection method and apparatus - Google Patents

Abstract

(57) [Summary] [PROBLEMS] To surely execute a color nonuniformity inspection of an entire effective portion of an inspection target image. SOLUTION: A transmittance image (inspection target image) composed of an effective portion Ia corresponding to the object and an invalid portion Ib outside the effective portion Ia obtained by imaging an object having a periodic pattern (A)
When inspecting the color unevenness of the periodic pattern by image processing
Based on an effective image Ie cut out using an effective area E which is a maximum rectangle inscribed in the mask area M of the mask image (B), the effective portion Ia of the transmittance image is divided into eight parts around the image Ie.
In the direction, a symmetric periodic image (D) arranged so that adjacent images have a symmetrical relationship with each other is created, and a range corresponding to the effective portion Ia is filtered and emphasized with respect to the symmetric periodic image (D). An image (E) is created, and color unevenness is determined based on the masked enhanced image (F) created by masking the enhanced image (E) with the mask image (B).

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a method and an apparatus for inspecting color unevenness defects, and more particularly to a periodic pattern having a light transmitting property on a substrate, such as a shadow mask used for a cathode ray tube of a color television and a color filter used for a liquid crystal display. The present invention relates to a color unevenness defect inspection method and apparatus suitable for detecting a color unevenness defect caused by disturbance of the uniformity of the pattern in a product on which is formed.

[0002]

2. Description of the Related Art Industrial products in which a periodic pattern in which minute openings are repeatedly arranged are formed include a shadow mask used for a cathode ray tube of a color television and a color filter used for a liquid crystal display. In such an industrial product, since it is important that the formed periodic aperture is uniform, the uniformity of the periodic pattern is determined by the color (luminance) caused by the disturbance.
Inspection is performed based on whether or not unevenness has occurred.

As a technique for inspecting a periodic aperture pattern formed in such a shadow mask or a color filter, an object is imaged by an image input device (imaging means) such as a CCD camera or an imaging tube. For example, Japanese Patent Application Laid-Open No. 6-229736 proposes an image processing apparatus that detects color unevenness defects by performing image processing on the obtained inspection target image.

FIG. 8 is a schematic front view showing a main part of an inspection apparatus applied to such a color unevenness defect inspection. This inspection apparatus irradiates illumination light from a light source 12 to a back side of a sample (object) W placed on a stage 10 via a diffusion plate 14 and a diffusion sheet 14A laminated thereon, An image input unit 18 including a CCD camera 16 that captures transmitted light on the front side of W is provided, and an image processing unit 20 that processes image data input by the camera 16 is provided.

FIG. 9 shows the configuration of the whole inspection apparatus.
The inspection apparatus roughly includes an inspection processing unit 22, a man-machine interface unit 24, and a machine-machine interface unit 26, and a device control unit 28 that manages the entire operation of each functional unit included in each of the units 22 to 26. And The inspection processing unit 22 includes the image input unit 18 as a functional unit and the image processing unit 20 that processes image data input by the image input unit 18. Similarly, the man-machine interface unit 24 An information display unit 30 for displaying a result processed by the image processing unit 20, an interpersonal operation unit 32 for exchanging information with an operator, a machine / machine interface unit 26, a belt conveyor for conveying an object; (Not shown) etc., each of which includes a machine interlocking unit 34 for exchanging information with an external machine.
26 to 26 are managed by the device control unit 28 as described above.

[0006] Each of these functional units will be described in detail. An area sensor camera or a line sensor camera can be used as the CCD camera 16 of the image input unit 18. Etc. can also be used.

As the image processing unit 20, a dedicated image processing device, a personal computer, or the like can be used. or,
The information display unit 30 provides the operator with the inspection progress status,
It has the function of presenting inspection results, counting results, history of past inspection results, etc., and displaying captured images, images in the course of processing, or images after processing, such as CRT monitors, liquid crystal monitors, and LED arrays. Etc. are available.

The interpersonal operation unit 32 (1) accepts an input operation required for an inspection from an operator, (2) sets characteristics (size, etc.) of the inspection object, and (3) an image processing unit 20. Set adjustment values (filter size, etc.), (4)
It has a function of setting an adjustment value (shutter speed and the like) of the image input unit 18, and can use a mechanical button, a touch panel, a keyboard, a mouse, and the like.

The mechanical interlocking unit 34 synchronizes with an external device at the time of automatic inspection, for example, synchronizes the supply of the inspection target to the image input unit 18 with a timing, etc., and instructs the distribution apparatus to be inspected (inspection) based on the inspection result. It has a function of issuing an instruction to sort and sort the target, stopping the supply to the inspection unit, and the like. This includes RS-232C, RS-422, GPIB (General Pur
pose Interface Bus), LAN (Ethernet),
Parallel I / O, relays, etc. can be used. Then, a device control unit 28 for managing the operation of each of the functional units 22 to 26 described above.
For example, a dedicated device, a general-purpose sequencer, a personal computer, or the like can be used.

In the inspection apparatus, the CCD camera 16
The image of the sample (inspected object) W is imaged using the image processing apparatus, and the obtained image data is subjected to image processing, thereby inspecting the presence or absence of color unevenness of the periodic pattern formed on the sample W.

Generally, the color unevenness to be inspected appears as a slight change in gradation in image data. Therefore, the presence / absence of color unevenness cannot be determined by simply performing simple binarization processing on the image data of the inspection target image. Therefore, conventionally, image data enhancement processing is performed to enhance the color unevenness of the inspection target image, and thereafter, the image in which the color unevenness is enhanced by the processing is subjected to simple binarization processing to perform the color unevenness processing. Is determined to detect a color unevenness defect.

[0012] The enhancement process executed here can be realized by filtering the image data using a spatial filter such as a differential filter. At this time, the detection performance can be improved by assuming the shape of the color unevenness to be detected and setting the shape of the filter in advance for each shape. FIG. 10 conceptually shows the features of this emphasis processing.

FIG. 10A shows an image to be inspected having the size of a vertical Im pixel and a horizontal In pixel input as an image.
For convenience, the area shown in white color is composed of an effective part (area where the inspection object exists) Ia and an invalid part (area where the inspection object does not exist) Ib indicated by a hatched area around its outside. .

When the color unevenness existing in the effective portion Ia is emphasized, a spatial filter for emphasizing processing as shown in the image of FIG. 1B is applied to the effective portion Ia. This filter is a secondary differential filter composed of the size of each element (pixel) of 2Km + 1 in height and 2Kn + 1 in width.
Shows a specific example when Km = 3 and Kn = 2.

The emphasis process (filtering process) using this filter multiplies each pixel of the entire effective portion Ia by the value of each element of the filter by the gradation value of the corresponding pixel, and sums the sum to the central pixel. This is equivalent to executing an operation of replacing the grayscale value with the grayscale value.

However, in the image to be inspected, the effective portion Ia, which is the region where the object exists, is finite, so that the ineffective portion Ib outside the effective portion Ia is required to have a vertical Km pixel and a horizontal Kn required for the filtering process. Assuming an area of the number of pixels, assuming the pixel value of the area to be a zero value (gradation value 0), the emphasis distance by the differential filter having a negative coefficient value is performed. Therefore, although the enhancement processing by this filtering processing is highly effective for inspecting subtle color unevenness, since the image data is discontinuous at the boundary of the effective portion Ia, it is indicated by a broken line in FIG. As shown, a distortion R called ringing occurs in the width of the vertical Km pixels and the horizontal Kn pixels in the peripheral region of the effective portion Ia, and a correct inspection result cannot be obtained in the region where the distortion R occurs. .

As a countermeasure, conventionally, a process of excluding a range in which the above-described distortion R has occurred from the inspection target has been performed. Hereinafter, this exclusion processing will be described in detail when the inspection target is a shadow mask. FIG. 12 shows an outline of a processing procedure up to creation of a determination image in this case.
Indicates an image of an image in a corresponding main image processing stage.

In the inspection apparatus shown in FIG. 8, first, in step 1, a sample (shadow mask) W is picked up by the CCD camera 16 to obtain sample image (transmitted light image) data. The light source image data is obtained by imaging only the light source without the sample.

Next, in step 3, by dividing the sample image data by the light source image data, a transmittance image (image to be inspected) which is not affected by shading existing in the light source 13 itself is created. FIG. 13 (A) shows an image of the transmittance image, which corresponds to FIG. 10 (A). Similarly, Ia is an effective portion and Ib is an invalid portion. To explain the transmittance image, assuming that I1 is light source image data captured in a state without a sample, I is sample image data captured by inserting a sample, and I0 is image data representing a dark current of the CCD camera 16, the sample W The transmittance T at the upper point can be calculated by the following equation (1).

T = (I−I 0) / (I 1 −I 0) (1)

Here, I, I0, and I1 are pixel data at the corresponding positions. By performing this calculation for each pixel, it is possible to obtain transmittance image data that is not affected by shading of the light source or its fluctuation. Can be.

When the transmittance image data is created by a normal CCD camera, a CCD camera with a built-in electronic shutter is used, and an image is taken by setting a sample with the electronic shutter in a shutter open state as an imaging condition setting method.
The brightness of the light source was adjusted so as to be close to the saturation exposure of the D camera, then the sample was removed, and the shutter time was shortened until the light amount did not exceed and the saturation exposure was approached, and the shutter time at that time was set to tc Assuming that the shutter time at the time of opening is to, a transmittance image can be obtained by the following equation (2). These calculations are performed by calculation between images after each image data is recorded in the frame memory by the image processing unit 20.

T = {(I−I 0) / (I 1 −I 0)} × (tc / to) (2)

Next, in step 4, the above step 3
The transmittance image (data), which is the image to be inspected created in the above, is binarized by a predetermined threshold value, and the valid part Ia is 255 and the invalid part I is
b is set to a gradation value of 0, and the pixel values are set to 1 and 0, respectively.
A mask image as shown in FIG. On the other hand, the transmittance image created in step 3 is subjected to a smoothing process (not shown) in order to remove minute fluctuations (noise), and thereafter, the color unevenness of the smoothed image is emphasized. In step 5, a second-order differentiation process using the spatial filter is performed in step 5.
An enhanced image as shown in FIG. 13C corresponding to (C) is created.

Next, in step 6, the above step 4
The effective portion side (pixel value 1) of the mask image of FIG. 13B created in step (b) is contracted so as to cover the distortion (ringing) region R occurring in the emphasized image created in step 5 above. . That is, the mask area M corresponding to the invalid portion Ib is expanded as shown in FIG. Then, in step 7, the emphasized image of FIG.
(E), a masking image of the enhanced image is created, and a simple binarizing process is performed on the masking image in the same manner as described above in the next step 8. In this manner, a judgment image is created and a color unevenness defect is inspected.

As described in detail above, when filtering is performed on an image to be inspected by using a spatial filter having a negative filter coefficient, it is effective for enhancing color unevenness, but it is effective for enhancing image unevenness. (Ringing) R is generated in an appropriate region. The range of the distortion R changes depending on the order (size: Km, Kn) of the filter.
There is a feature that the range becomes wider as the order is larger.

Therefore, as described above, in such a distortion region, since correct image data as an emphasized image cannot be obtained, the range in which the distortion R is generated as shown in FIG. Conventionally, mask processing is performed to exclude the inspection target from inspection.

[0028]

However, in the above-described method of masking the distorted area and excluding it from the inspection target, even if the judgment processing can be performed only on the correct data, the defective area remains in the excluded area. Even if there is color unevenness, the problem that it cannot be detected still remains.

The present invention has been made to solve the above-mentioned conventional problems, and provides a color unevenness defect inspection method and apparatus capable of reliably performing a color unevenness inspection on the entire effective portion of an image to be inspected. That is the task.

[0030]

SUMMARY OF THE INVENTION According to the present invention, an image of an object having a periodic pattern is picked up and inputted, and an image to be inspected comprising an effective portion corresponding to the object and an invalid portion outside the image is processed. In a color unevenness defect inspection method for inspecting color unevenness present in a periodic pattern, an enhanced image is created by performing a filtering process on the inspection target image with a spatial filter,
In inspecting a color unevenness defect using the enhanced image, an outside of an effective portion of the inspection target image is filled up using image data of a peripheral portion of the effective portion to create an enhancement target image, and the enhancement target image is formed. On the other hand, the above problem is solved by creating an emphasized image by filtering a range corresponding to the effective portion.

According to the present invention, there is further provided an image pickup means for picking up an image of an object having a periodic pattern and inputting an image to be inspected comprising an effective portion corresponding to the object and an invalid portion outside the effective portion. A color unevenness defect inspection apparatus comprising: an image processing unit configured to perform image processing on the target image to detect color unevenness. An enhancement target image creating means for creating an enhancement target image by using the image data of the peripheral portion of the image to be enhanced, and filtering the range corresponding to the effective portion with a spatial filter on the enhancement target image to form the enhancement image. The above-mentioned problem is similarly solved by providing an emphasizing means for creating and a judging means for judging a color unevenness defect based on the created emphasized image.

That is, in the present invention, an enhancement target image is created by filling the outside of the effective portion of the inspection target image using the image data of the peripheral portion of the effective portion, and the enhancement process is performed on the target image. Therefore, it is possible to prevent the occurrence of distortion in the peripheral portion of the effective portion, and to inspect the entire effective portion, that is, the entire range in which the inspection target exists.

[0033]

Embodiments of the present invention will be described below in detail with reference to the drawings.

FIG. 1 is a block diagram showing a main part of an image processing section provided in a color unevenness defect inspection apparatus according to an embodiment of the present invention.

The inspection apparatus of this embodiment has substantially the same overall configuration as that shown in FIG. 9 and only the image processing section 20 has the configuration shown in FIG. Accordingly, the image input unit 18 is substantially the same as that shown in FIG.

In the present embodiment, the image processing unit 20 passes the light source through the diffusion plate 14 and the diffusion sheet 14A in a state where the sample (inspection object) W is not on the stage 10 of the image input unit 18 shown in FIG. A light source image memory 202 for storing a light source image obtained by imaging the light source 12, a transmitted light image memory 204 for storing a transmitted light image obtained by imaging the sample W while the sample W is on the stage 10, Memory 202,
A transmittance calculating unit 206 that creates a transmittance image (data) based on the image data read from the memory 204, a transmittance image memory 208 that stores the transmittance image, and a A mask creation unit 210 for creating a mask image and a mask image memory 212 for storing the mask image are built in.

The image processing section 20 further extracts an effective range corresponding to the largest rectangle inscribed in the effective portion in the transmittance image (inspection image) based on the image data from the mask image memory 212. A range extracting unit 214, an inverted coordinate memory 216 for storing each corner coordinate of the maximum rectangle as inverted coordinates based on the coordinate data defining the effective range, and a transmittance image read from the transmittance image memory 208. The effective image cut out based on the effective range, the upper and lower, left, right,
Inverted copy unit (enhancement target image creating means) 218 that creates a symmetrical periodic image (enhancement target image) by inversion copying in eight oblique directions, a symmetrical periodic image memory 220 that stores the image data, and memory 220 An enhancement processing unit 222 that enhances a symmetrical periodic image read from a memory, an enhancement image memory 224 that stores an enhanced image after processing,
24 is read from the mask image memory 2
12, an enhanced image mask processing unit 226 that performs a mask process using the mask image read from the memory 12, a masked enhanced image memory 228 that stores the image data after the mask process, and a masked enhanced image that is read from the memory 228. A decision processing unit 232 for performing a color irregularity defect decision process based on a decision condition set by the decision condition setting unit 230 by a normal method, and a decision image memory 234 for storing the processed image. .

Next, the operation of the present embodiment will be described with reference to the flowcharts of FIGS. The characteristics of the image at the main image processing stage are shown in FIG.
This will be described with reference to FIG.

First, the processing from step 1 to step 4 is performed by the transmittance calculator 206 and the mask generator 210. Steps 1 to 4 are the same as the processes of steps 1 to 4 shown in FIG. As a result of the processing in each of the above steps, the transmittance image (A) and the mask image (B) shown in FIG. 4 are obtained. Since these two images are the same as those shown in FIGS. 13A and 13B, the same reference numerals are given and the description is omitted.

Next, at step 5, the reverse copy unit 2
A symmetric periodic image is created by 18. This step 5
Are as shown in FIG. That is, first, using the mask image read out from the mask image memory 212 by the effective range extraction unit 214, as shown in an enlarged view in FIG. E is extracted as E (step 51), and the straight lines L1 to L4 passing through each side of the effective range E are set as inversion axes. (Step 52). Here, the maximum rectangle inscribed in the mask area M is extracted as the effective range E, which is equivalent to extracting the maximum rectangle inscribed in the effective portion Ia of the transmittance image. The reason for using the maximum rectangular effective image inscribed in the effective portion Ia in this way is that the effective portion Ia is usually not a perfect straight line around the effective portion Ia.
An object of the present invention is to facilitate image processing such as a target operation.

Next, in order to create a symmetric periodic image,
Using the effective range E, the largest rectangular portion is cut out from the effective portion Ia of the transmittance image in FIG. 4A as an effective image Ie, and the inversion axes L1 to L are centered on the effective image Ie.
In step 53, the reverse copying unit 218 reversely copies the effective image Ie so that the adjacent images are in an inverted relationship with each other in eight directions, up, down, left, right, and oblique. As shown in FIG. 4D, a total of nine symmetrical periodic images are created and stored in the symmetrical periodic image memory 220.

FIG. 5 shows an image of the relationship between the effective image Ie and the symmetric periodic image. FIG. 3A shows an effective image I.
At e, the direction is indicated by R for convenience, and FIG. 2B shows a symmetric periodic image centered on the effective image Ie. As can be seen from FIG. 8B, the rectangular images are all symmetrical with respect to L1 to L4, and (upper and lower) and (left and right) are the same, respectively.
(Diagonal) are all the same and can be created by copying.

As described above, the symmetric periodic image is created in step 5, but the enhancement processing unit 222 creates a emphasized image by filtering the entire effective image Ie at the center of the symmetric periodic image (step 6). ). This filtering process is the same as that in step 5 in FIG. 12, but here, as shown in FIG. 4E, a different calculation range F depending on the size of the spatial filter used.
Can be set (compensated) by image data based on the central effective image Ie. Therefore, as shown in FIG. 6A, the effective image Ie and the inverted image on the left side of the effective image Ie, and as shown in FIG. are doing.

Therefore, according to the conventional method, FIG.
As shown in FIG. 7B, an area having a gradation value of 0 is set outside the boundaries G1 and G2 for filtering, as shown in FIG. As a result, the distortion (ringing) region R occurs at the peripheral portion as described in detail with reference to FIGS. 10 and 13. In the present embodiment, however, the continuous gradation values are all present on the four sides around the effective image Ie. Is obtained, the distortion region R does not occur even if the entire range same as the effective portion Ia is emphasized.

Next, the enhanced image mask processing section 226
4E, the enhanced image shown in FIG. 4E is masked using the mask image shown in FIG. 4B, and the masked enhanced image shown in FIG. Is created (step 7). Since the mask image has no distortion R in the enhanced image, the mask image is not shrunk as in the related art, and is used in the mask area M having the same size as the invalid portion Ib in FIG. Can be. For the masking image created in this way, the determination processing unit 232
Creates a judgment image similar to the conventional one (step 8),
Make a decision.

According to the present embodiment described in detail above, it is possible to prevent the occurrence of the distortion region R on the periphery of the range corresponding to the effective portion Ia. Inspection can be performed reliably.

Although the present invention has been specifically described above, the present invention is not limited to the above-described embodiment, and can be variously modified without departing from the gist thereof.

For example, the emphasis target image to be filtered is not limited to the symmetric periodic image, but is an image in which the tone value is substantially continuous between the effective image Ie and the image in eight directions around the effective image Ie. If it is, there is no particular limitation. Therefore, when there is substantially no difference in the tone values near the inversion axes L1 and L2 or near L3 and L4, the effective image Ie is not inverted around the effective image Ie in eight directions. ,
The valid image Ie itself may be simply copied and arranged. In this case, the emphasis target image can be easily created in a short time.

Further, the outer peripheral area necessary for filtering is made to have the same gradation value by simply using the gradation value of the pixel located at the peripheral end of the effective image Ie or the effective portion Ia, for example, the average value of several pixels. It may be set to a value.

[0050]

As described above, according to the present invention,
The color nonuniformity inspection occurring in the periodic pattern can be reliably executed for the entire effective portion of the inspection target image.

[Brief description of the drawings]

FIG. 1 is a block diagram illustrating features of an image processing unit included in a color unevenness defect inspection apparatus according to an embodiment of the present invention.

FIG. 2 is a flowchart illustrating an outline of a processing procedure performed by the inspection apparatus according to the embodiment;

FIG. 3 is a flowchart showing details of step 5 in FIG. 2;

FIG. 4 is an image diagram showing characteristics of an image during processing according to the embodiment;

FIG. 5 is an explanatory diagram showing an image of a symmetric periodic image adopted in the present embodiment.

FIG. 6 is an explanatory diagram showing characteristics of the same symmetric periodic image.

FIG. 7 is an explanatory diagram showing an image of a conventional enhancement processing method.

FIG. 8 is an explanatory diagram showing a main configuration of the inspection apparatus.

FIG. 9 is a block diagram schematically showing the overall configuration of the inspection apparatus.

FIG. 10 is an explanatory view showing a conventional process of enhancing an image to be inspected.

FIG. 11 is an explanatory diagram showing an example of a spatial filter.

FIG. 12 is a flowchart showing a processing procedure performed by a conventional inspection device.

FIG. 13 is an image diagram showing characteristics of an image being processed by a conventional inspection apparatus.

[Explanation of symbols]

 Reference Signs List 10 stage 12 light source 14 diffusion plate 14A diffusion sheet 16 CCD camera 18 image input unit 20 image processing unit W sample (inspection target)

 ──────────────────────────────────────────────────続 き Continuing on the front page (72) Atsushi Okazawa, 1-1-1, Ichigaya-Kagacho, Shinjuku-ku, Tokyo Inside Dai Nippon Printing Co., Ltd. No. 1-1 F-term in Dai Nippon Printing Co., Ltd. (reference) 2G051 AA41 AA90 AB20 AC04 CA03 CA04 CB02 EA11 EA12 ED01 ED04 ED14 5B057 AA01 BA02 CA01 CA08 CA12 CA16 CB01 CB06 CB12 CB16 CE06 CE08 CE09 CE12 DA03 DB02 DB06 DC06 5C061 BB02 EE11

Claims (14)

[Claims] An image processing is performed on an inspection target image, which is obtained by imaging an object having a periodic pattern and includes an effective portion corresponding to the target and an invalid portion outside the effective portion, and exists in the periodic pattern. In the color non-uniformity defect inspection method for inspecting color non-uniformity, an enhancement target image in which an outside of an effective portion of the inspection target image is filled using image data of a peripheral portion of the effective portion is created. A color unevenness defect inspection method, wherein an enhanced image is created by filtering a range corresponding to the effective portion with a spatial filter, and a color unevenness defect is inspected using the enhanced image. 2. The method according to claim 1, wherein the emphasis target image is created along a maximum rectangle inscribed in the effective portion, based on an effective image obtained by cutting out an inspection target image in the effective portion. Color unevenness defect inspection method. 3. The color unevenness according to claim 2, wherein the image to be enhanced is a symmetric periodic image in which images adjacent to each other in eight directions around the effective image are arranged so as to be symmetrical with each other. Defect inspection method. 4. The color unevenness defect inspection method according to claim 2, wherein the image to be enhanced is a copy image obtained by copying the effective image in eight directions around the effective image. 5. The image according to claim 2, wherein the image to be enhanced is an extended image obtained by extending image data of a corresponding peripheral end of the effective image in eight directions around the effective image. Color unevenness defect inspection method. 6. The method according to claim 1, wherein the created emphasis target image is subjected to a masking process using a mask image composed of a binary image in which the effective portion is 1 and the outside invalid portion is 0. Color unevenness defect inspection method. 7. The inspection target image according to claim 1, wherein the inspection target image is a transmittance image obtained by dividing a target image obtained by capturing a transmitted light image obtained by illuminating the target object from behind with a light source by a light source image obtained by capturing only the light source. A color non-uniformity defect inspection method. 8. An image pickup means for picking up an image of an object having a periodic pattern, and an image to be inspected consisting of an effective portion corresponding to the imaged object and an ineffective portion outside the image, image processing for color unevenness. A color non-uniformity defect inspection apparatus, comprising: an image processing unit that detects an error in the image to be inspected. The image processing unit emphasizes the outside of an effective portion of the inspection target image by using image data of a peripheral portion of the effective portion. An emphasis target image creating unit that creates a target image; an emphasis unit that creates an enhanced image by filtering a range corresponding to the effective portion with respect to the emphasis target image using a spatial filter; A determination unit for determining whether a color unevenness defect has occurred on the basis of the color unevenness defect inspection apparatus. 9. The image processing apparatus according to claim 8, wherein the emphasis target image creating means is configured to generate the emphasis target image based on an effective image obtained by cutting out the inspection target image in the effective part along a maximum rectangle inscribed in the effective part. A color non-uniformity defect inspection apparatus characterized in that the inspection is performed in the following manner. 10. The color unevenness according to claim 9, wherein the emphasis target image is a symmetric periodic image in which images adjacent to each other in eight directions around the effective image are arranged so as to be symmetrical with each other. Defect inspection equipment. 11. The color non-uniformity defect inspection apparatus according to claim 9, wherein the emphasis target image is a copy image obtained by copying the effective image in eight directions around the effective image. 12. The image according to claim 9, wherein the image to be enhanced is an extended image obtained by extending image data of a corresponding peripheral end of the effective image in eight directions around the effective image. Color unevenness defect inspection device. 13. A mask processing means according to claim 8, wherein said created emphasis target image is masked by a mask image consisting of a binary image in which said effective part is 1 and said outside invalid part is 0. A color unevenness defect inspection device. 14. The inspection target image according to claim 8, wherein the inspection target image is a transmittance image obtained by dividing a target image obtained by capturing a transmitted light image obtained by illuminating an object from behind with a light source by a light source image obtained by capturing only the light source. A color non-uniformity defect inspection apparatus.