JP5135899B2 - Periodic pattern unevenness inspection method and unevenness inspection apparatus - Google Patents

Description

  The present invention relates to a method and apparatus for inspecting pattern unevenness in an inspection object having a periodic pattern. A periodic pattern refers to an aggregate of patterns having a constant interval. For example, a striped periodic pattern in which patterns are arranged at a predetermined period (pitch) or an opening pattern is two-dimensional with a predetermined period. A matrix-like pattern or the like arranged in a regular manner. For example, a color filter, a black matrix, a photomask, or the like corresponds to the inspection object having a periodic pattern, and the present invention can be used.

  The irregularity pattern in the periodic pattern is usually difficult to find by individual pattern inspection because fine pattern deviations are often regularly arranged, but when looking at the periodic pattern as a whole, It is a defect that is manifested in a different state from other normal parts.

  Visual inspection has been widely performed as an inspection for mura defects. For example, the unevenness can be visually recognized by observing the periodic pattern through transmitted light or reflected light from an oblique direction or the like with respect to the periodic pattern surface of the object to be inspected.

  However, since the visual inspection has a problem that the inspection result varies depending on the proficiency level of the worker, for example, a nonuniformity inspection apparatus such as Patent Document 1 or Patent Document 2 has been devised. In these unevenness inspection apparatuses, a transmittance image is captured using transmission illumination or plane illumination coaxial with the imaging camera, and the unevenness is detected by comparing the intensity (brightness) of light in each image. In other words, in the periodic pattern, originally, the light intensity difference between the uneven portion and the normal portion is small, that is, the image with low contrast is devised by processing the intensity difference to extract the uneven portion by expanding the difference. We are inspecting.

  However, in the above-described prior art, it is not possible to improve the contrast between the uneven portion and the normal portion in imaging unevenness of the lattice-like periodic pattern (for example, the black matrix of the color filter), particularly unevenness of the periodic pattern having a large opening. Even when the intensity difference processing is devised, there is a problem that the inspection in the case of an image having a low contrast of the original image can only achieve a lower inspection ability than the visual sensory inspection.

  On the other hand, due to the increase in fine display and electronic components with a bright screen, the periodic pattern tends to be miniaturized or increase in aperture ratio. In the future, there will be a need for a method and apparatus for inspecting the periodic pattern irregularity for a black matrix having a finer shape and a larger opening. That is, the conventional inspection based only on the intensity (brightness) of light based on the amplitude of light is a limit.

  Therefore, for the purpose of providing a periodic unevenness inspection apparatus capable of imaging and detecting a periodic pattern, for example, black matrix unevenness stably and with high accuracy, illumination light is irradiated to the object to be inspected, and An inspection apparatus for inspecting the generated transmitted diffraction light with an image has been proposed. In the normal part of the periodic pattern, since the shape and pitch of the openings are constant, they interfere with each other and generate strong diffracted light in a certain direction. On the other hand, since the shape and pitch of the opening are unstable in the uneven portion, diffracted light is generated with various intensities in various directions according to the shape and pitch. This inspection apparatus detects uneven portions from the difference in contrast of diffracted light. However, the diffraction intensity changes depending on the irradiation angle of the illumination light, the wavelength of the illumination light, the shape of the opening, the pitch, and the like. Furthermore, the difference in contrast between the normal part and the uneven part due to the diffracted light is often very small. Therefore, in this apparatus, in order to obtain an image satisfying a desired inspection sensitivity, it is necessary to set a complicated inspection recipe for each type of object to be inspected, and the inspection accuracy varies due to a difference in proficiency between workers. It can happen.

The following publicly known documents are described.
JP 2002-148210 A JP 2002-350361 A

  The present invention solves the above-described problem, and easily determines the presence or absence of unevenness in the periodic pattern of an object to be inspected, and suppresses variations in inspection accuracy due to differences in proficiency among workers. This is the issue.

The invention according to claim 1 made to solve the above problem is a non-uniformity inspection method for inspecting whether a periodic pattern formed on an object to be inspected has non-uniformity , wherein the periodicity The pattern has an opening through which light is transmitted, and an imaging process for capturing an inspection image at a plurality of irradiation angles with respect to the object to be inspected, and a maximum value and a minimum value of the pixel value of the inspection area in the inspection image A first image analysis step of selecting one or a plurality of inspection images from the first image feature quantity at each illumination angle based on the pixel values in the inspection region of the inspection image selected by the first image analysis step; A second image analysis step of selecting a specific inspection image from the second image feature amount based on variation, and an evaluation for determining the presence or absence of unevenness in the object to be inspected based on the first image analysis step and the second image analysis step And having a process Is unevenness inspection method characterized. By performing this inspection method, it is possible to easily determine the presence or absence of unevenness in the periodic pattern of the object to be inspected, and to suppress variations in inspection accuracy due to differences in proficiency among workers. For this reason, it has become possible to stably and highly accurately detect unevenness of an object to be inspected having a periodic pattern.

According to a second aspect of the present invention, the object to be inspected is any one of a photomask, a color filter, and a black matrix, and the unevenness has a regular pattern with a fine pattern shift different from the periodic pattern. Is a non-uniformity caused by the arrangement
When a white isolated point appears in the inspection image, a noise removing step including a step of removing the white isolated point as a noise from the inspection region is provided before the first image analysis step. The defect inspection method according to claim 1. By having a noise removal step before image processing, it is possible to prevent erroneous determination due to factors other than defects due to noise, and to improve inspection accuracy.

The unevenness inspection according to claim 1, wherein the second image feature amount is calculated by a standard deviation or a sample standard deviation of a pixel value in the inspected region. Is the method. This is preferable because the second image feature amount is directly expressed as the magnitude of variation in pixel values.

The invention according to claim 4 is an unevenness inspection apparatus for detecting unevenness of an object to be inspected having a periodic pattern, wherein the periodic pattern includes an opening through which light can be transmitted , Irradiating means for irradiating light; irradiation angle control means for irradiating light at an arbitrary illumination angle to the object to be inspected; imaging means for acquiring an inspection image of the object to be inspected at each illumination angle; Image processing means connected to the imaging means, and evaluation means for determining the presence or absence of unevenness in the object to be inspected, the image processing means having a maximum pixel value of the inspected area in the inspected image A first image analysis unit that selects one or a plurality of inspection images from image feature values at each illumination angle based on the value and the minimum value; and a pixel value of the inspection region selected by the first image analysis unit Second drawing based on variation A second image analyzing means for selecting a particular test image from the feature, an unevenness inspection apparatus characterized by comprising: a determining evaluation means the presence or absence of unevenness in the object to be inspected from the particular test image. By selecting an inspection image from two parameters, a first image feature amount based on the maximum value and the minimum value of the pixel value, and a second image feature amount based on the variation amount, and determining the presence or absence of a defect, the inspection accuracy is improved. Can be improved. In addition, only the inspection image in which the first image feature amount exceeds a predetermined threshold needs to be subjected to the calculation for calculating the second image feature amount, so that the calculation process can be reduced. Further, since the presence or absence of unevenness can be evaluated based only on the image information of the inspected object to be inspected, the inspection accuracy does not vary due to the difference in proficiency between workers.

According to a fifth aspect of the present invention, the object to be inspected is any one of a photomask, a color filter, and a black matrix, and the image processing means has the object to be inspected when a white isolated point appears in the inspection image. The unevenness inspection apparatus according to claim 4, further comprising a noise removing unit including a function capable of removing noise from the inspection region.
The invention according to claim 6 is the unevenness inspection apparatus according to claim 4 or 5 , wherein the irradiating means irradiates parallel light or light close to parallel light. By using parallel light or light close to parallel light, the incident angle of the irradiation light can be limited to a certain direction, and the diffraction angle can be set in a certain range to improve the contrast of the inspection image. . Furthermore, variation in the light amount distribution can be suppressed.

The invention according to claim 7 is the unevenness inspection apparatus according to any one of claims 4 to 6, characterized in that, in the irradiation means, the wavelength of light to be irradiated is limited to a certain range. By limiting the wavelength of the irradiated light to a certain range, the diffraction angle at the normal part can be more restricted to a specific direction, and the diffraction angle is determined to be within a certain range, thereby improving the contrast of the inspection image. Because it can.

Incidentally invention according to claim 4-7 is also characterized in that the image processing means includes a noise removing means for removing noise of the inspection image. By including the noise removing unit, it is possible to prevent erroneous determination due to noise other than unevenness and to improve inspection accuracy.

The invention according to claim 8 is the unevenness inspection apparatus according to any one of claims 4 to 7 , wherein the second image feature amount is based on a standard deviation or a sample standard deviation of a pixel value in the region to be inspected. is there. This is preferable because the second image feature amount is directly expressed as the magnitude of variation in pixel values.

  As described above, by performing the inspection method according to the present invention, it is possible to easily determine the presence or absence of unevenness in the periodic pattern of the object to be inspected, and to suppress variations in inspection accuracy due to differences in proficiency among workers. Can do. For this reason, it has become possible to stably and highly accurately detect unevenness of an object to be inspected having a periodic pattern. Furthermore, since the effect of increasing the S / N ratio between the normal part and the uneven part is devised by devising the noise removal process and the irradiation light, the inspection accuracy can be improved by making the uneven defect appear more prominent.

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

<Inspection device>
FIG. 1 shows an example of an inspection apparatus according to the present invention. The inspection apparatus of the present invention includes a stage 12 for installing an inspection object 13 having a periodic pattern, a light source 11 as an illuminating means for the inspection object 3, and an imaging for acquiring a diffraction image from the inspection object. An element 14 (for example, a CCD area camera, a CCD line camera, etc.) and an image processing means connected to the imaging element and performing image processing for detecting defects on the acquired diffraction image, and further, an acquired image or A display device for displaying the processed image is provided. Although not shown, an irradiation angle control means for irradiating light at an arbitrary angle with respect to the object to be inspected is connected to the light source.

  As the light source 11, for example, a metal halide lamp, a halogen lamp, a xenon lamp, or the like can be used. If the light from the light source is diffused and irradiated, even within the same region to be inspected, the irradiation energy varies depending on the irradiated portion, causing a reduction in the SN ratio of the inspection image. Therefore, it is preferable to irradiate parallel light or light close to parallel light (substantially parallel light). If such light is used, the incident angle of the irradiation light can be limited to a certain direction, and the contrast of the inspection image can be improved by setting the diffraction angle within a certain direction. Furthermore, variation in the light amount distribution can be suppressed. The substantially parallel light can be obtained, for example, by arranging a lens or the like between the light source and the stage 12.

  In addition, by selectively limiting the wavelength of the light emitted from the light source 11 using a bandpass filter or the like, the contrast between the normal part and the uneven part can be further emphasized. This is because although the diffraction angle varies depending on the wavelength of light, it is possible to limit the diffraction angle in the normal part to a specific direction by limiting the wavelength of the irradiated light to a certain range.

  The light irradiated from the light source 11 onto the object 13 generates diffracted light having an intensity depending on the projection wavelength, the pattern pitch of the periodic pattern, the aperture ratio of the periodic pattern, and the like depending on the illumination angle. The intensity distribution of this diffracted light is imaged by the imaging means 14 to obtain an inspection image. The illumination angle of light is changed by a certain amount, and the intensity distribution of the diffracted light is imaged each time, and an inspection image at each illumination angle is acquired.

  FIG. 2 shows a schematic diagram of the inspection image. A region occupied by the periodic pattern in the inspection image 21 is an inspection region 22. At the time of imaging, the light intensity of the light source 11 or the exposure setting of the imaging means 14 are adjusted so that the average value of the luminance values (pixel values) for each pixel in the inspection area in each inspection image is uniform. Take an image. The captured inspection image is sent to an arithmetic device having an image processing means connected to the image sensor 14. The image processing means includes a noise removing means described below, a first image analysis means for calculating the first image feature quantity, a second image analysis means for calculating the second image feature quantity, and determining unevenness. Evaluation means.

  In addition to the unevenness to be detected by the inspection method according to the present invention, dust or the like may adhere to the inspected object 13 depending on the inspection environment, and they may appear in the inspection image 21 as noise. The noise often appears as a white isolated point in the inspection image 21. In order to remove the white isolated point from the region to be inspected 22, a method of performing pixel expansion / contraction on the inspection image at each angle is effective. Assuming that the distribution of pixel values in the inspection region is a normal distribution, the average value of the pixel values in the inspection region 22 is equal to or greater than three times the standard deviation of the pixel values in the inspection region 22 The influence of the noise can be reduced by removing pixels having the brightness of. Therefore, it is preferable that the image processing means of the present invention has the image processing means for removing noise as described above. In addition, the object to be inspected according to the present invention is often produced in a dust-free environment such as a clean room. Therefore, it is desirable that the present invention is also carried out in a dust-free environment.

・ Noise removal means The shape and pitch of the openings are constant in the normal part of the periodic pattern, so that they interfere with each other and generate strong diffracted light in a certain direction, whereas the shape and pitch of the openings are not uniform in the uneven part. In order to be stable, diffracted light is generated with various intensities in various directions according to the shape and pitch. However, the contrast difference in diffraction intensity between the normal portion and the uneven portion varies greatly depending on the illumination angle of the light source 11. Therefore, in the present invention, unevenness becomes obvious by extracting an image in which the difference between the maximum value and the minimum value of the pixel value in the inspection region 22 is a predetermined threshold or more from the inspection images for each illumination angle. Narrow inspection images. Further, the difference in diffraction intensity between the normal portion and the uneven portion due to the difference in the illumination angle of the light source 11 appears not only as a contrast difference of the uneven portion 23 but also as a pixel area difference of the uneven portion 23. That is, it can be said that as the variation in the pixel value in the region to be inspected 22 increases, the unevenness appears more remarkably.

First Image Analysis Means As specific processing contents, first, the maximum pixel value and the minimum pixel value are detected for the inspection region of the inspection image for each illumination angle. For each illumination angle, a value obtained by subtracting the minimum pixel value from the maximum pixel value is calculated as the first image feature amount, and the graph is plotted with the illumination angle on the horizontal axis and the first image feature amount on the vertical axis. Then, one or a plurality of inspection images in which the obtained first image feature value is a value equal to or greater than a predetermined threshold Th ₁ are narrowed down as inspection image candidates having a high diffraction intensity. In the example of the first image analysis result schematic diagram 31 in FIG. 3, the inspection image having the first image feature amount equal to or more than the line indicated by Th ₁ corresponds to this. At this time, by using the image processing means for noise removal described above in advance, it is possible to suppress erroneous determination due to factors other than defects due to noise, so that the detection accuracy is improved.

Second image analysis means Next, the variation amount of the pixel value of one or a plurality of inspection images narrowed down by the first image analysis means described above is used as the second image feature amount, and one sheet having the strongest diffracted light intensity. Second image analysis means for narrowing down the inspection images. Specifically, as the parameter of the variation amount, unbiased variance, sample variance, standard deviation that is the square root thereof, sample standard deviation, or the like can be used. In particular, if a standard deviation or a sample standard deviation (which can be approximated to a standard deviation when the number of pixels in the region to be inspected is large) is used, the second image feature amount is expressed as it is as the magnitude of variation in pixel values. It is.

Of the one or multiple images narrowed down by the first image analyzing means, the image having the maximum value of the second image feature value is set as the representative inspection image of the object to be inspected. The maximum value of the second image feature amount is because the pixel value has the largest variation and unevenness appears remarkably. In the example of the second image analysis result schematic diagram 32 in FIG. 3, the inspection having the second image feature amount A _max having the largest value among the inspection images in the region of Th ₁ or more in the first image analysis result schematic diagram 31. This is the case with images.

Evaluation means Further, the inspection apparatus according to the present invention further comprises a defect determination means for determining the presence / absence of unevenness in the inspected object based on the first image analysis means and the second image analysis means described above, and the second image with a possible value of the characteristic amount is the predetermined threshold value Th ₂ or more, determining that there is unevenness in the test subject. In the example of the second image analysis result schematic diagram 32 of FIG. 3, because it has a value of the second image characteristic amount exceeding the threshold value Th _2, it is determined that there is uneven.

<Inspection method>
FIG. 4 shows a flow of a series of processing until the presence / absence of unevenness of the periodic pattern is determined using the inspection method of the present invention. First, an object to be inspected is placed on a stage, and imaging conditions (camera focus, camera aperture, initial camera exposure time, etc.), imaging area (inspected area, etc.), illumination conditions (initial light intensity of light source 11, initial illumination angle) , Band pass filter, etc.). Then, an inspection image at the set initial illumination angle is captured. It is determined whether or not the average value of pixel values in a region to be inspected in a captured inspection image is within a predetermined range. If it deviates from the predetermined range, the imaging conditions and the irradiation light quantity of the light source 11 are adjusted, and imaging is performed again. If it is within the predetermined range, the illumination angle is changed and the inspection image is acquired again. This is repeated until there is no more illumination angle to be imaged next.

  A white isolated point is removed from the inspection image taken at each illumination angle by the above-described noise removing means. The difference between the maximum value and the minimum value of the pixel values in the inspection region of each inspection image is calculated to obtain the first image feature amount. Then, one or a plurality of inspection images in which the value of the first image feature value obtained by the first image analysis means is a value equal to or greater than a predetermined threshold is narrowed down as inspection image candidates having a high diffraction intensity. Subsequently, a variation amount of the inspection image narrowed down by the first image analysis unit is calculated to obtain a second image feature amount. If the maximum value of the second image feature amount is equal to or greater than a predetermined threshold value, it is determined that the periodic pattern of the object to be inspected is uneven. Finally, the inspection result and unevenness information are output to the display screen 16.

  By selecting an inspection image from the two parameters of the first image feature amount based on the maximum value and the minimum value of the pixel value and the second image feature amount based on the variation amount as described above, and determining whether or not there is a defect Inspection accuracy can be improved. In addition, only the inspection image in which the first image feature amount exceeds a predetermined threshold needs to be subjected to the calculation for calculating the second image feature amount, so that the calculation process can be reduced.

The result of the Example when the inspection method according to the present invention is applied to a photomask is presented in FIG. The photomask of the object to be inspected is composed of a matrix pattern in which opening patterns are two-dimensionally arranged at a predetermined cycle. In FIG. 5, the horizontal axis of the image analysis means embodiment 51 represents the irradiation angle, and the vertical axis represents the first image feature value obtained by subtracting the minimum pixel value from the maximum pixel value. The first image feature quantity Filter illumination angle is a predetermined threshold value above T ₁ as a strong inspection image candidate diffraction intensity. In the image analysis means embodiment 52, the horizontal axis represents the illumination angle, and the vertical axis represents the first image feature quantity that is the standard deviation of the pixel value. From the angle region narrowed down by the first image analysis means, the angle having the maximum second image feature amount is found, and the inspection image at that angle is set as a representative image in which unevenness appears most remarkably. In FIG. 5, the illumination angle at the point A where the first image feature amount is equal to or greater than the predetermined threshold and the second image feature amount is the maximum is the illumination angle at which the unevenness appears most prominently. Then, comparing the second image characteristic amount with a predetermined threshold value T ₂ at point A. When inspected shown in FIG. 5, since the second image characteristic amount at the point A is higher than the T _2, in the cyclic pattern it is determined unevenness exists.

It is a figure showing an example of an inspection device concerning the present invention. It is a figure which shows the external appearance of the test | inspection image which concerns on this invention. It is a figure which shows the relationship between the illumination angle and 1st image feature-value which concern on this invention, and an illumination angle and 2nd image feature-value. It is a figure which shows the flow of implementation of the inspection method which concerns on this invention. It is a figure which shows the relationship between the illumination angle and 1st image feature-value in the photomask which performed the nonuniformity test | inspection in the Example of this invention, and the illumination angle and 2nd image feature-value.

Explanation of symbols

DESCRIPTION OF SYMBOLS 11 ... Light source 12 ... Stage 13 ... Inspected object 14 ... Imaging means 15 ... Image processing apparatus 16 ... Display screen 21 ... Inspection image 22 ... Inspected area 23 ... Unevenness 31 ... First image analysis result schematic diagram 32 ... Second image Analysis result schematic diagram 51... First image analysis means embodiment 52... Second image analysis means embodiment

Claims (8)

An unevenness inspection method for inspecting whether a periodic pattern formed on an object to be inspected has unevenness ,
The periodic pattern has an opening through which light passes,
An imaging step of imaging an inspection image at a plurality of irradiation angles with respect to the object to be inspected;
A first image analysis step of selecting one or a plurality of inspection images from the first image feature amount at each illumination angle based on the maximum value and the minimum value of the pixel value of the inspection region in the inspection image;
A second image analysis step of selecting a specific inspection image from a second image feature amount based on variations in pixel values in the inspection region of the inspection image selected by the first image analysis step;
Based on the first image analysis step and the second image analysis step, an evaluation step for determining the presence or absence of unevenness in the inspected object,
A method for inspecting unevenness , characterized by comprising: The object to be inspected is one of a photomask, a color filter, and a black matrix,
The unevenness is unevenness that occurs because fine pattern deviations are regularly arranged with a period different from the periodic pattern,
When a white isolated point appears in the inspection image, a noise removing step including a step of removing the white isolated point as a noise from the inspection region is provided before the first image analysis step. The unevenness inspection method according to claim 1. 3. The unevenness inspection method according to claim 1, wherein the second image feature amount is calculated by a standard deviation or a sample standard deviation of a pixel value in a region to be inspected. A non- uniformity inspection apparatus for detecting nonuniformity of an object to be inspected having a periodic pattern,
The periodic pattern includes an opening that can transmit light;
Irradiating means for irradiating the object to be inspected;
An irradiation angle control means for irradiating light at an arbitrary illumination angle on the object to be inspected;
Imaging means for obtaining an inspection image of the object to be inspected at each illumination angle;
Image processing means connected to the imaging means;
An evaluation means for determining the presence or absence of unevenness in the object to be inspected;
And the image processing means includes:
First image analysis means for selecting one or a plurality of inspection images from image feature amounts at each illumination angle based on the maximum value and the minimum value of the pixel value of the inspection region in the inspection image;
Second image analysis means for selecting a specific inspection image from a second image feature quantity based on variations in pixel values of the inspection area selected by the first image analysis means;
Evaluation means for determining the presence or absence of unevenness in the object to be inspected from the specific inspection image;
A nonuniformity inspection apparatus comprising: The object to be inspected is one of a photomask, a color filter, and a black matrix,
5. The unevenness according to claim 4, wherein the image processing unit includes a noise removing unit including a function capable of removing a white isolated point as noise from the inspection region when a white isolated point appears in the inspection image. Inspection device. The unevenness inspection apparatus according to claim 4, wherein the irradiation unit emits parallel light or light close to parallel light. The unevenness inspection apparatus according to any one of claims 4 to 6, wherein in the irradiation means, the wavelength of light to be irradiated is limited to a certain range. The unevenness inspection apparatus according to claim 4, wherein the second image feature amount is based on a standard deviation or a sample standard deviation of a pixel value in the inspection area.

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