Chip surface defect detection method, device and computer readable storage medium

Abstract

The present application is applicable to the field of chip detection technology, and provides a chip surface defect detection method, device and computer-readable storage medium. The method obtains multiple original images of the chip to be detected and determines the first clarity of the original image; and determines the edge area of ​​the original image and determines the second clarity of the edge area; and determines the third clarity based on the first clarity and the second clarity, so as to determine the image to be processed with higher third clarity from the multiple original images. Since the third clarity combines the first clarity and the second clarity, the edge area and the original image in the image to be processed with higher third clarity are both clear. The cracks in the edge area of ​​the target image determined based on the image to be processed are also obvious. Therefore, it is easy to detect the cracks in the edge area when detecting the target image to prevent missed detection.

Description

Technical Field

[0001] The present application belongs to the field of chip detection technology, and in particular, relates to a chip surface defect detection method, device and computer-readable storage medium. Background Art

[0002] With the continuous development of electronic technology, the semiconductor industry has attracted more and more attention, and chip manufacturing and testing have become a hot topic in the semiconductor field. Usually, after the chip is manufactured, it is necessary to detect defects on the chip surface, for example, to detect whether there are defects such as cracks on the chip surface.

[0003] The prior art generally uses a microscope to perform manual or automatic detection of defects on the chip surface. Among them, automatic detection is usually achieved by autofocusing. The specific process is: after focusing once, the microscope stays at a certain distance from the chip surface to shoot the chip surface, obtain an image of the chip surface, and then automatically identifies the cracks on the chip surface in the image through a defect detection algorithm.

[0004] In the above-mentioned automatic detection method of chip surface defects, the image captured by the microscope is the image when the chip surface is clearest. However, the applicant found that when the chip surface is clearest, some cracks on the chip surface are not clear, so that such unclear cracks cannot be detected, resulting in missed detection. Summary of the invention

[0005] The embodiments of the present application provide a chip surface defect detection method, device and computer-readable storage medium, aiming to solve the technical problem that existing chip surface defect detection methods may miss detection.

[0006] In a first aspect, an embodiment of the present application provides a method for detecting chip surface defects, comprising:

[0007] Acquire multiple original images of the chip to be detected, and determine a first clarity of the original images;

[0008] determining an edge region of the original image, and determining a second definition of the edge region;

[0009] Determining a third definition of the original image according to the first definition and the second definition;

[0010] Based on the third definition, N images to be processed are determined from the multiple original images; the definition of any image to be processed is higher than the definition of other original images, the other original images are original images other than the image to be processed among the multiple original images, and N is a positive integer;

[0011] A target image is determined according to the N images to be processed, and surface defects of the chip to be inspected are detected based on the target image.

[0012] The embodiment of the present application obtains multiple original images of the chip to be detected and determines the first clarity of the original image; determines the edge area of ​​the original image and determines the second clarity of the edge area; and determines the third clarity based on the first clarity and the second clarity, thereby determining the image to be processed with higher third clarity from the multiple original images. Since the third clarity combines the first clarity and the second clarity, the edge area and the original image in the image to be processed with higher third clarity are both clear. The cracks in the edge area of ​​the target image determined based on the image to be processed are also obvious, so it is easy to detect the cracks in the edge area when detecting the target image to prevent missed detection.

[0013] In combination with the first aspect, in an implementation of the embodiment of the present application, obtaining multiple original images of the chip to be detected includes:

[0014] A plurality of original images captured by a lens of a microscope imaging device at different distances from the surface of the chip to be detected are obtained.

[0015] In this implementation, since the original image is captured when the distance between the lens and the chip to be detected changes, the original image can reflect the focusing effects at different distances, thereby capturing images of different focusing conditions in the maximum range.

[0016] In combination with the first aspect, in an implementation of the embodiment of the present application, a plurality of original images captured by a lens of a microscope imaging device at different distances from the surface of a chip to be detected are obtained, including:

[0017] Acquire a first original image captured when the lens is at a first distance from the surface; when the lens is at the first distance from the surface, the focal plane of the lens is between the surface and the lens;

[0018] Acquire a second original image captured when the lens is at a second distance from the surface; when the lens is at the second distance from the surface, the surface is between the focal plane of the lens and the lens;

[0019] A third original image captured when the lens is at a third distance from the surface is obtained; when the lens is at the third distance from the surface, the focal plane of the lens coincides with the surface.

[0020] In this implementation, the original image at least includes the image taken when the focal plane of the lens is between the surface of the chip to be detected and the lens, the image taken when the surface of the chip to be detected is between the focal plane of the lens and the lens, and the image taken when the surface of the chip to be detected coincides with the focal plane of the lens, so it actually includes the images before and after the surface of the chip to be detected coincides with the focal plane of the lens. The clearest image of the crack usually appears in the image before and after the surface of the chip to be detected coincides with the focal plane of the lens, so this embodiment can ensure that the original image taken includes the clearest image of the crack, achieving a better detection effect.

[0021] In combination with the first aspect, in an implementation of the embodiment of the present application, determining a first definition of the original image includes:

[0022] Perform fast Fourier transform on the pixel values ​​of the original image to obtain the high-frequency information of the original image;

[0023] A first definition is determined based on the high frequency information.

[0024] This implementation method can reflect the clarity of the original image through high-frequency information, which is more accurate.

[0025] In combination with the first aspect, in an implementation of the embodiment of the present application, determining the second clarity of the edge area includes:

[0026] Determine gray value difference data of edge area;

[0027] Gaussian fitting is performed on the gray value difference data to obtain the variance; the variance is negatively correlated with the second clarity;

[0028] A second resolution is determined based on the variance.

[0029] The second clarity is calculated by using the algorithm of the implementation method, which can more accurately reflect the clarity of the edge area and improve the accuracy of clarity judgment.

[0030] In combination with the first aspect, in an implementation of the embodiment of the present application, determining a target image according to N images to be processed includes:

[0031] When N=1, the image to be processed is determined as the target image;

[0032] When N>1, the pixel values ​​of the target image are calculated according to the pixel values ​​of the image to be processed, the position parameters of the edge region of the image to be processed and the weight of the image to be processed, and the target image is generated according to the pixel values ​​of the target image.

[0033] This implementation method can synthesize multiple images into one image through the above algorithm, so as to enhance the adaptability of clarity, improve the contrast of cracks, and improve the effect of crack detection.

[0034] In combination with the first aspect, in an implementation of the embodiment of the present application, detecting surface defects of a chip to be detected based on a target image includes:

[0035] The target image is processed by a preset defect detection algorithm to obtain the detection results of surface defects.

[0036] In a second aspect, an embodiment of the present application provides a device for detecting chip surface defects, comprising:

[0037] An acquisition module, used for acquiring a plurality of original images of the chip to be detected, and determining a first clarity of the original images;

[0038] A processing module, used for determining an edge region of the original image and determining a second definition of the edge region;

[0039] The processing module is further used to determine a third definition of the original image according to the first definition and the second definition;

[0040] The processing module is further used to determine N to-be-processed images from the multiple original images based on the third definition; the definition of any to-be-processed image is higher than the definition of other original images, the other original images are original images other than the to-be-processed image among the multiple original images, and N is a positive integer;

[0041] The processing module is also used to determine a target image according to the N images to be processed, and detect surface defects of the chip to be detected based on the target image.

[0042] In combination with the second aspect, in an implementation of the embodiment of the present application, the acquisition module is also used to: acquire a plurality of original images captured by the lens of the microscope imaging device at different distances from the surface of the chip to be detected.

[0043] In conjunction with the second aspect, in an implementation of the embodiment of the present application, the acquisition module is further used to:

[0044] Acquire a first original image captured when the lens is at a first distance from the surface; when the lens is at the first distance from the surface, the focal plane of the lens is between the surface and the lens;

[0045] Acquire a second original image captured when the lens is at a second distance from the surface; when the lens is at the second distance from the surface, the surface is between the focal plane of the lens and the lens;

[0046] A third original image captured when the lens is at a third distance from the surface is obtained; when the lens is at the third distance from the surface, the focal plane of the lens coincides with the surface.

[0047] In conjunction with the second aspect, in an implementation manner of the embodiment of the present application, the processing module is further configured to:

[0048] Perform fast Fourier transform on the pixel values ​​of the original image to obtain the high-frequency information of the original image;

[0049] A first definition is determined based on the high frequency information.

[0050] In conjunction with the second aspect, in an implementation manner of the embodiment of the present application, the processing module is further configured to:

[0051] Determine gray value difference data of edge area;

[0052] Gaussian fitting is performed on the gray value difference data to obtain the variance; the variance is negatively correlated with the second clarity;

[0053] A second resolution is determined based on the variance.

[0054] In conjunction with the second aspect, in an implementation manner of the embodiment of the present application, the processing module is further configured to:

[0055] When N=1, the image to be processed is determined as the target image;

[0056] When N>1, the pixel values ​​of the target image are calculated according to the pixel values ​​of the image to be processed, the position parameters of the edge region of the image to be processed and the weight of the image to be processed, and the target image is generated according to the pixel values ​​of the target image.

[0057] In conjunction with the second aspect, in an implementation manner of the embodiment of the present application, the processing module is further configured to:

[0058] The target image is processed by a preset defect detection algorithm to obtain the detection results of surface defects.

[0059] In a third aspect, an embodiment of the present application provides a terminal device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the method of the first aspect when executing the computer program.

[0060] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method of the first aspect is implemented.

[0061] In a fifth aspect, an embodiment of the present application provides a computer program product, which, when executed on a terminal device, enables the terminal device to execute the method of the first aspect.

[0062] It can be understood that the beneficial effects of the second to fifth aspects mentioned above can be found in the relevant description of the first aspect mentioned above, and will not be repeated here.

[0063] Compared with the prior art, the embodiments of the present invention have the following beneficial effects:

[0064] The embodiments of the present application provide a method, device and computer-readable storage medium for detecting chip surface defects. The method obtains multiple original images of the chip to be detected and determines the first clarity of the original image; determines the edge area of ​​the original image and determines the second clarity of the edge area; and determines the third clarity based on the first clarity and the second clarity, thereby determining a third clarity image to be processed from multiple original images. Since the third clarity combines the first clarity and the second clarity, the edge area and the original image in the third clarity image to be processed are both clear. The cracks in the edge area of ​​the target image determined based on the image to be processed are also obvious. Therefore, it is easy to detect the cracks in the edge area when detecting the target image to prevent missed detection. BRIEF DESCRIPTION OF THE DRAWINGS

[0065] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0066] Figure 1 is a schematic structural diagram of a chip detection system in an embodiment of the present application;

[0067] Figure 2 This is a flow chart of a method for detecting chip surface defects in an embodiment of the present application;

[0068] Figure 3 is a schematic diagram of shooting conditions at different distances between the lens and the chip to be detected in an embodiment of the present application;

[0069] Figure 4 is a schematic diagram of shooting results at different distances between the lens and the chip to be detected in an embodiment of the present application;

[0070] Figure 5 is a schematic diagram of an image to be processed determined in an embodiment of the present application;

[0071] Figure 6 is a schematic diagram of a target image synthesized in an embodiment of the present application;

[0072] Figure 7 is a schematic diagram used to describe Gaussian fitting in an embodiment of the present application;

[0073] Figure 8 A schematic diagram of a chip surface defect detection device provided in an embodiment of the present application;

[0074] Fig. 9 A schematic diagram of a chip surface defect detection device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0075] In the following description, specific details such as specific system structures, technologies, etc. are provided for the purpose of illustration rather than limitation, so as to provide a thorough understanding of the embodiments of the present application. However, it should be clear to those skilled in the art that the present application may also be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to prevent unnecessary details from obstructing the description of the present application.

[0076] It should be understood that when used in the present specification and the appended claims, the term "comprising" indicates the presence of described features, wholes, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components and / or combinations thereof.

[0077] It should also be understood that the term “and / or” used in the specification and appended claims refers to any and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0078] As used in the specification and appended claims of this application, the term "if" can be interpreted as "when" or "uponce" or "in response to determining" or "in response to detecting", depending on the context. Similarly, the phrase "if it is determined" or "if [described condition or event] is detected" can be interpreted as meaning "uponce it is determined" or "in response to determining" or "uponce [described condition or event] is detected" or "in response to detecting [described condition or event]", depending on the context.

[0079] In addition, in the description of the present application specification and the appended claims, the terms "first", "second", "third", etc. are only used to distinguish the descriptions and cannot be understood as indicating or implying relative importance.

[0080] References to "one embodiment" or "some embodiments" etc. described in the specification of this application mean that one or more embodiments of the present application include specific features, structures or characteristics described in conjunction with the embodiment. Therefore, the statements "in one embodiment", "in some embodiments", "in some other embodiments", "in some other embodiments", etc. that appear in different places in this specification do not necessarily refer to the same embodiment, but mean "one or more but not all embodiments", unless otherwise specifically emphasized in other ways. The terms "including", "comprising", "having" and their variations all mean "including but not limited to", unless otherwise specifically emphasized in other ways.

[0081] Figure 1 FIG. 1 is a schematic structural diagram of a chip detection system in an embodiment of the present application. Figure 1 As shown, the chip detection system may include a microscope imaging device and a detection platform 1. The microscope imaging device includes a lens 3, an optical path 4, and a focal plane 5. A chip 2 to be detected is placed on the detection platform 1, and the microscope imaging device can control the lens 3 to aim at the chip 2 to be detected and shoot. For ease of understanding, the optical path 4 and the focal plane 5 of the lens 3 will be drawn in the embodiment of the present application. Among them, the focal plane 5 can also be called the object focal plane (The focal plane) or the front focal plane. The microscope imaging device controls the movement of the lens 3 and captures multiple images, then processes these images to obtain a target image, and finally detects the target image to determine the cracks on the chip surface.

[0082] Figure 2 Flow chart of the chip surface defect detection method in the embodiment of the present application. The process can be executed by a control device (not shown) of the microscope imaging device, and the control device can be arranged inside the microscope imaging device, or can be arranged outside the microscope imaging device and connected to the microscope imaging device, which is not particularly limited in the embodiment of the present application. Figure 2 As shown, the detection method of chip surface defects includes:

[0083] 201. Acquire multiple original images of a chip to be inspected, and determine a first clarity of the original images.

[0084] In the embodiment of the present application, the control device can move the lens 3 of the microscope imaging device up and down and capture multiple original images. For each original image, the first clarity of the original image can be determined by a first clarity evaluation function / clarity evaluation algorithm. The first clarity evaluation function / clarity evaluation algorithm can adopt a common algorithm or an algorithm provided in the embodiment of the present application, wherein the algorithm provided in the embodiment of the present application is as follows:

[0085] Perform Fast Fourier Transformation (FFT) on the pixel values ​​of the original image to obtain the high-frequency information of the original image; determine the first clarity based on the high-frequency information. It can be understood that the first clarity can describe the overall clarity of the original image. Generally, the higher the parameter value of the first clarity, the clearer the original image. The algorithm can reflect the clarity of the original image through high-frequency information, which is more accurate.

[0086] It is understandable that the up-and-down movement of the lens 3 in the embodiment of the present application may refer to the movement of the lens 3 in the vertical direction (direction of the main optical axis of the lens). Therefore, the up-and-down movement of the lens 3 may be only the up-and-down movement in the vertical direction, or may be the up-and-down movement superimposed with the vertical direction and the horizontal direction (i.e., the oblique direction movement).

[0087] In some embodiments, step 201 specifically includes: obtaining a plurality of original images captured by a lens of a microscope imaging device at different distances from the surface of the chip to be detected. Figure 3 As shown, the lens 3 can move up and down (generally from top to bottom), so that the distance between the lens 3 and the chip to be detected changes. During the distance change process, multiple original images can be captured, that is, Figure 4 The original images a, b, c, d and e are shown. The original images a to e are taken when the distance from the lens to the surface of the chip to be detected is gradually reduced.

[0088] In this embodiment, since the original image is captured when the distance between the lens 3 and the chip to be detected 2 changes, the original image can reflect the focusing effect at different distances, thereby capturing images of different focusing conditions in the maximum range.

[0089] Further, in some embodiments, step 201 includes the following steps:

[0090] 2011. Acquire a first original image captured when the lens is at a first distance from the surface; when the lens is at the first distance from the surface, the focal plane of the lens is between the surface and the lens;

[0091] For example, Figure 3 and Figure 4 As shown, in the shooting situations corresponding to the original image a and the original image b, the focal plane 5 of the lens 3 is between the surface of the chip 2 to be detected and the lens 3.

[0092] 2012. Acquire a second original image captured when the lens is at a second distance from the surface; when the lens is at the second distance from the surface, the surface is between the focal plane of the lens and the lens;

[0093] For example, Figure 3 and Figure 4 As shown, in the shooting situations corresponding to the original image d and the original image e, the surface of the chip 2 to be detected is between the focal plane 5 of the lens 3 and the lens 3, that is, the focal plane 5 of the lens 3 passes downward through the surface of the chip 2 to be detected.

[0094] 2013. Obtain a third original image captured when the lens is at a third distance from the surface; when the lens is at the third distance from the surface, the focal plane of the lens coincides with the surface.

[0095] For example, Figure 3 and Figure 4 As shown, in the shooting situation corresponding to the original image c, the surface of the chip 2 to be detected coincides with the focal plane 5 of the lens 3.

[0096] In this embodiment, the original image at least includes the image taken when the focal plane 5 of the lens 3 is between the surface of the chip 2 to be detected and the lens 3, the image taken when the surface of the chip 2 to be detected is between the focal plane 5 of the lens 3 and the lens 3, and the image taken when the surface of the chip 2 to be detected coincides with the focal plane 5 of the lens 3, and thus actually includes the images before and after the surface of the chip 2 to be detected coincides with the focal plane 5 of the lens 3. The clearest image of the crack usually appears in the image before and after the surface of the chip 2 to be detected coincides with the focal plane 5 of the lens 3, so this embodiment can ensure that the original image taken includes the clearest image of the crack, achieving a better detection effect.

[0097] 202. Determine an edge region of the original image, and determine a second definition of the edge region.

[0098] In the embodiment of the present application, the control device may determine the edge area of ​​the original image by an edge detection algorithm. The edge detection algorithm may include but is not limited to a canny edge detection algorithm, a Sobel edge detection algorithm, a Prewitt edge detection algorithm, etc., which is not limited in the embodiment of the present application.

[0099] In the embodiment of the present application, the control device can determine the clarity of the edge area by using a second clarity evaluation function / clarity evaluation algorithm. The second clarity evaluation function / clarity evaluation algorithm can use a common algorithm or an algorithm provided in the embodiment of the present application, wherein the algorithm provided in the embodiment of the present application is as follows:

[0100] The edge is the location where the grayscale value is discontinuous in the image. In order to analyze edge information, the prior art has proposed many edge models, such as the step model, the straight line model, and the T-shaped model. The embodiment of the present application adopts the algorithm of the Gaussian edge model. The algorithm first determines the grayscale value difference data of the edge area; then performs Gaussian fitting on the grayscale value difference data to obtain the variance, wherein the variance is negatively correlated with the second definition; finally, the second definition is determined based on the variance. Specifically, Figure 7 As shown, the grayscale of the edge area is shown in the top picture, the cross section is shown in the middle picture, and the first-order derivative of the differential data of the cross section is obtained as shown in the bottom picture. Finally, according to the first-order derivative, the corresponding mean and variance can be obtained by Gaussian fitting of the differential data. The second clarity can be determined according to the variance, and the variance is negatively correlated with the second clarity. When the variance is the smallest, it is the clearest.

[0101] By using the algorithm provided in the embodiment of the present application to calculate the second clarity, the clarity of the edge area can be more accurately reflected, thereby improving the accuracy of clarity judgment.

[0102] 203. Determine a third definition of the original image according to the first definition and the second definition.

[0103] In an embodiment of the present application, a weighted average method can be used to determine the third clarity of the original image based on the first clarity and the second clarity. Specifically, the third clarity = first clarity × weight 1 + second clarity × weight 2. It can be understood that weight 1 and weight 2 are pre-set constants. Using the method of the present application to determine the third clarity can more realistically reflect the comprehensive clarity of the edge area and the original image, where cracks are generally identified as edge areas. Therefore, the embodiment of the present application actually takes into account the clarity of the cracks, so that images with clear cracks can be detected to prevent missed cracks.

[0104] 204. Determine N to-be-processed images from the plurality of original images based on the third definition.

[0105] In the embodiment of the present application, the control device can sort the original images according to the size of the third definition, and then select the first N original images with the highest third definition as the images to be processed, where N is a positive integer. The above method can make the definition of any image to be processed higher than the definition of other original images, and the other original images are original images other than the image to be processed among the multiple original images. The embodiment of the present application does not exclude other methods to achieve the above effects, and these methods all belong to the scope of protection of the embodiment of the present application.

[0106] For example, Figure 4 and Figure 5 As shown, among original image a, original image b, original image c, original image d, and original image e, the first three original images with the highest third clarity are original image a, original image b, and original image c. The control device can determine that original image a, original image b, and original image c are the images to be processed based on the third clarity.

[0107] 205. Determine a target image according to the N images to be processed, and detect surface defects of the chip to be inspected based on the target image.

[0108] In the embodiment of the present application, the control device can adopt different processing methods according to the value of N. Specifically, when N=1, the image to be processed is determined as the target image. Exemplarily, if only the original image b is determined as the image to be processed, the original image b is the target image, and the surface defects of the chip b to be detected can be detected based on the original image b.

[0109] When N>1, the control device can calculate the pixel value of the target image according to the pixel value of the image to be processed, the position parameter of the edge area of ​​the image to be processed and the weight of the image to be processed, and generate the target image according to the pixel value of the target image. Specifically, it can be calculated by the following formula:

[0110]

[0111] Where D is the pixel value of the target image, A i is the pixel value of the i-th image to be processed, B i is the position parameter of the edge area of ​​the i-th image to be processed, C i is the preset weight of the i-th image to be processed. i is a preset value, B i It can be determined by an edge detection algorithm, and the embodiment of the present application does not limit the edge detection algorithm to be used.

[0112] The pixel values ​​of the target image can be calculated by the above formula algorithm, and then the target image can be generated according to the pixel values ​​of the target image. Figure 5 and Figure 6 As shown, the original image a, the original image b, and the original image c are collectively referred to as image x. It can be seen that the cracks in image x are clearer.

[0113] The embodiment of the present application can combine multiple images into one image through the above-mentioned formula algorithm to enhance the adaptability of clarity, improve the contrast of cracks, and improve the effect of crack detection.

[0114] In the embodiment of the present application, the surface defects of the chip to be detected are detected based on the target image, including: processing the target image by a preset defect detection algorithm to obtain the detection result of the surface defects. The specific defect detection algorithm can adopt the common algorithm in the prior art, and the embodiment of the present application does not limit this.

[0115] The embodiment of the present application obtains multiple original images of the chip to be detected and determines the first clarity of the original image; determines the edge area of ​​the original image and determines the second clarity of the edge area; and determines the third clarity based on the first clarity and the second clarity, thereby determining the image to be processed with higher third clarity from the multiple original images. Since the third clarity combines the first clarity and the second clarity, the edge area and the original image in the image to be processed with higher third clarity are both clear. The cracks in the edge area of ​​the target image determined based on the image to be processed are also obvious, so it is easy to detect the cracks in the edge area when detecting the target image to prevent missed detection.

[0116] Figure 8A schematic diagram of a chip surface defect detection device provided in an embodiment of the present application. The chip surface defect detection device 800 includes:

[0117] Acquisition module 801, used to execute or implement the above Figure 2 Corresponding to step 201 in each embodiment;

[0118] Processing module 802 is used to execute or implement the above Figure 2 These correspond to steps 202, 203, 204 and 205 in the respective embodiments.

[0119] Specifically, the acquisition module 801 is used to acquire multiple original images of the chip to be detected and determine the first clarity of the original images;

[0120] The processing module 802 is used to determine the edge area of ​​the original image and determine the second definition of the edge area;

[0121] The processing module 802 is further configured to determine a third definition of the original image according to the first definition and the second definition;

[0122] The processing module 802 is further configured to determine N to-be-processed images from the plurality of original images based on the third definition; the definition of any to-be-processed image is higher than the definition of the other original images, the other original images are original images other than the to-be-processed image among the plurality of original images, and N is a positive integer;

[0123] The processing module 802 is further used to determine a target image according to the N images to be processed, and detect surface defects of the chip to be inspected based on the target image.

[0124] In some embodiments, the acquisition module 801 is further used to: acquire a plurality of original images captured by a lens of a microscope imaging device at different distances from the surface of the chip to be detected.

[0125] In some embodiments, the acquisition module 801 is further used to:

[0126] Acquire a first original image captured when the lens is at a first distance from the surface; when the lens is at the first distance from the surface, the focal plane of the lens is between the surface and the lens;

[0127] Acquire a second original image captured when the lens is at a second distance from the surface; when the lens is at the second distance from the surface, the surface is between the focal plane of the lens and the lens;

[0128] A third original image captured when the lens is at a third distance from the surface is obtained; when the lens is at the third distance from the surface, the focal plane of the lens coincides with the surface.

[0129] In conjunction with the second aspect, in an implementation of the embodiment of the present application, the processing module 802 is further configured to:

[0130] Perform fast Fourier transform on the pixel values ​​of the original image to obtain the high-frequency information of the original image;

[0131] A first definition is determined based on the high frequency information.

[0132] In some embodiments, the processing module 802 is further configured to:

[0133] Determine gray value difference data of edge area;

[0134] Gaussian fitting is performed on the gray value difference data to obtain the variance; the variance is negatively correlated with the second clarity;

[0135] A second resolution is determined based on the variance.

[0136] In some embodiments, the processing module 802 is further configured to:

[0137] When N=1, the image to be processed is determined as the target image;

[0138] When N>1, the pixel values ​​of the target image are calculated according to the pixel values ​​of the image to be processed, the position parameters of the edge region of the image to be processed and the weight of the image to be processed, and the target image is generated according to the pixel values ​​of the target image.

[0139] In some embodiments, the processing module 802 is further configured to:

[0140] The target image is processed by a preset defect detection algorithm to obtain the detection results of surface defects.

[0141] Fig. 9 Schematic diagram of a chip surface defect detection device provided in an embodiment of the present application. The device 900 includes a memory 902, a processor 901, and a computer program 903 stored in the memory 902 and executable on the processor 901. When the processor 901 executes the computer program 903, the following is achieved: Figure 2 The corresponding methods of each embodiment.

[0142] It should be noted that the information interaction, execution process, etc. between the above-mentioned devices / units are based on the same concept as the method embodiment of the present application. Their specific functions and technical effects can be found in the method embodiment part and will not be repeated here.

[0143] The technicians in the relevant field can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example for illustration. In practical applications, the above-mentioned function allocation can be completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiment can be integrated in a processing unit, or each unit can exist physically separately, or two or more units can be integrated in one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this application. The specific working process of the units and modules in the above-mentioned system can refer to the corresponding process in the aforementioned method embodiment, which will not be repeated here.

[0144] An embodiment of the present application further provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps in the above-mentioned method embodiments can be implemented.

[0145] An embodiment of the present application provides a computer program product. When the computer program product runs on a mobile terminal, the mobile terminal can implement the steps in the above-mentioned method embodiments when executing the computer program product.

[0146] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present application implements all or part of the processes in the above-mentioned embodiment method, which can be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium, and the computer program can implement the steps of the above-mentioned various method embodiments when executed by the processor. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium can at least include: any entity or device that can carry the computer program code to the camera / terminal device, recording medium, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, RandomAccess Memory), electric carrier signal, telecommunication signal and software distribution medium. For example, a USB flash drive, a mobile hard disk, a magnetic disk or an optical disk. In some jurisdictions, according to legislation and patent practice, computer-readable media cannot be electric carrier signals and telecommunication signals.

[0147] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0148] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0149] In the embodiments provided in the present application, it should be understood that the disclosed devices / network equipment and methods can be implemented in other ways. For example, the device / network equipment embodiments described above are merely schematic. For example, the division of the modules or units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0150] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0151] The embodiments described above are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, a person skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application.

Claims

1. A method for detecting chip surface defects, It is characterized in that include: Acquire multiple original images of the chip to be detected, and determine a first clarity of the original images; Determine an edge area of ​​the original image, and determine a second definition of the edge area; Determine a third definition of the original image according to the first definition and the second definition by adopting a weighted average method; Based on the third definition, N images to be processed are determined from the multiple original images; the definition of any one of the images to be processed is higher than that of other original images, the other original images are original images other than the image to be processed among the multiple original images, and N is a positive integer; Determine a target image according to the N images to be processed, and detect surface defects of the chip to be inspected based on the target image; The step of determining a target image according to the N images to be processed includes: When N=1, the image to be processed is determined as the target image; When N>1, the pixel value of the target image is calculated according to the pixel value of the image to be processed, the position parameter of the edge area of ​​the image to be processed and the weight of the image to be processed, and the target image is generated according to the pixel value of the target image, which is specifically calculated by the following formula: ； Where D is the pixel value of the target image, For the i The pixel values ​​of the image to be processed, is the position parameter of the edge area of ​​the i-th image to be processed, is the preset weight of the i-th image to be processed; The step of acquiring a plurality of original images of the chip to be detected comprises: Acquire a first original image captured when the lens is at a first distance from the surface; when the lens is at the first distance from the surface, the focal plane of the lens is between the surface and the lens; Acquire a second original image captured when the lens is at a second distance from the surface; when the lens is at the second distance from the surface, the surface is between the focal plane of the lens and the lens; A third original image captured when the lens is at a third distance from the surface is acquired; when the lens is at the third distance from the surface, the focal plane of the lens coincides with the surface.

2. The method according to claim 1, It is characterized in that The determining the first definition of the original image comprises: Performing a fast Fourier transform on the pixel values ​​of the original image to obtain high-frequency information of the original image; The first definition is determined according to the high frequency information.

3. The method according to claim 1, It is characterized in that The determining the second clarity of the edge area includes: Determining grayscale value difference data of the edge area; Performing Gaussian fitting processing on the gray value difference data to obtain a variance; the variance is negatively correlated with the second clarity; The second definition is determined according to the variance.

4. The method according to claim 1, It is characterized in that The detecting the surface defects of the chip to be detected based on the target image comprises: The target image is processed by a preset defect detection algorithm to obtain the detection result of the surface defect.

5. A device for detecting chip surface defects, It is characterized in that include: An acquisition module, used for acquiring a plurality of original images of the chip to be detected, and determining a first clarity of the original images; A processing module, used for determining an edge region of the original image and determining a second definition of the edge region; The processing module is further configured to determine a third definition of the original image according to the first definition and the second definition by adopting a weighted average method; The processing module is further configured to determine N to-be-processed images from the plurality of original images based on the third definition; the definition of any one of the to-be-processed images is higher than the definition of the other original images, the other original images are original images other than the to-be-processed image among the plurality of original images, and N is a positive integer; The processing module is further used to determine a target image according to the N images to be processed, and detect surface defects of the chip to be inspected based on the target image; The processing module is further used for: When N=1, the image to be processed is determined as the target image; When N>1, the pixel value of the target image is calculated according to the pixel value of the image to be processed, the position parameter of the edge area of ​​the image to be processed and the weight of the image to be processed, and the target image is generated according to the pixel value of the target image, which is specifically calculated by the following formula: ； Where D is the pixel value of the target image, For the i The pixel values ​​of the image to be processed, is the position parameter of the edge area of ​​the i-th image to be processed, is the preset weight of the i-th image to be processed; The acquisition module is also used for: Acquire a first original image captured when the lens is at a first distance from the surface; when the lens is at the first distance from the surface, the focal plane of the lens is between the surface and the lens; Acquire a second original image captured when the lens is at a second distance from the surface; when the lens is at the second distance from the surface, the surface is between the focal plane of the lens and the lens; A third original image captured when the lens is at a third distance from the surface is acquired; when the lens is at the third distance from the surface, the focal plane of the lens coincides with the surface.

6. A terminal device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, It is characterized in that When the processor executes the computer program, the method according to any one of claims 1 to 4 is implemented.

7. A computer-readable storage medium storing a computer program, It is characterized in that When the computer program is executed by a processor, the method according to any one of claims 1 to 4 is implemented.

Images