Method, device and apparatus for identifying authenticity of integrated circuit chips based on wafer images

Abstract

The present invention relates to a method for identifying the authenticity of an integrated circuit chip based on a wafer image, comprising obtaining a first wafer image of a sample chip and a second wafer image of a chip to be tested; obtaining a first variation curve based on the first wafer image, and obtaining a second variation curve based on the second wafer image; and determining the authenticity of the chip to be tested based on the first variation curve and the second variation curve. The present invention minimizes the influence of artificial noise in wafer images and improves the recognition rate of chip authenticity. The present invention also relates to a device for identifying the authenticity of an integrated circuit chip based on a wafer image, a storage medium, and a device.

Description

Technical Field

[0001] The present invention relates to the field of integrated circuit technology, and in particular to a method, device and equipment for identifying the authenticity of integrated circuit chips based on wafer images. Background Art

[0002] Since the opening, cleaning and photographing of integrated circuit chip wafers are all manual operations, it is inevitable that a lot of human interference noise will be introduced into the chip wafer image during the operation, such as epoxy resin residue contamination on the wafer surface when opening the cover, and light changes when taking pictures. Ordinary image matching methods, such as image fingerprint matching methods, do not focus on the problem of human noise in compatible images, and will treat the human noise as image pixels, resulting in problems such as low recognition accuracy. Summary of the invention

[0003] The technical problem to be solved by the present invention is to provide a method, device and equipment for identifying the authenticity of integrated circuit chips based on wafer images in view of the deficiencies in the prior art.

[0004] The technical solution of the present invention to solve the above technical problems is as follows:

[0005] A method for identifying the authenticity of an integrated circuit chip based on a wafer image, comprising:

[0006] Acquire a first wafer image of a sample chip and a second wafer image of a chip to be tested;

[0007] Obtaining a first variation curve according to the first wafer image, and obtaining a second variation curve according to the second wafer image;

[0008] The authenticity of the chip to be inspected is determined based on the first variation curve and the second variation curve.

[0009] The beneficial effect of the invention of the method is: a method for identifying the authenticity of integrated circuit chips based on wafer images is proposed, including obtaining a first wafer image of a sample chip and a second wafer image of a chip to be tested; obtaining a first variation curve according to the first wafer image, and obtaining a second variation curve according to the second wafer image; and determining the authenticity of the chip to be tested based on the first variation curve and the second variation curve. The invention minimizes the influence of artificial noise in wafer images and improves the recognition rate of chip authenticity.

[0010] Based on the above technical solution, the present invention can also be improved as follows.

[0011] Further, obtaining a first variation curve according to the first wafer image and obtaining the second variation curve according to the second wafer image specifically includes:

[0012] Performing filtering, smoothing and scaling processing on the first wafer image to obtain a first wafer image matrix;

[0013] Performing filtering, smoothing and scaling processing on the second wafer image to obtain a second wafer image matrix, wherein the first wafer image matrix and the second wafer image matrix have the same matrix size;

[0014] Calculating the coefficient of variation of rows and columns of the first wafer image matrix row by row and column by column to obtain the first variation curve;

[0015] The coefficient of variation of the rows and columns of the second wafer image matrix is ​​calculated row by row and column by column to obtain the second variation curve, wherein the first variation curve and the second variation curve have the same length, and the order of corresponding points on the first variation curve and the second variation curve is also the same.

[0016] Further, calculating the coefficient of variation of rows and columns of the first wafer image matrix row by row and column by column to obtain the first variation curve specifically includes:

[0017] The pixel value x of each row or column in the first wafer image matrix i Enter into formula Obtaining a first standard deviation σ1 of each row or column of the first wafer image matrix, obtaining a first coefficient of variation corresponding to each row or column according to the first standard deviation σ1 and a first average value μ1, and obtaining the first variation curve based on all the obtained first coefficients of variation, wherein N is the number of elements in each row or column of the first wafer image matrix, and obtaining the first average value μ1 according to the pixel value of each row or column in the first wafer image matrix;

[0018] Calculating the coefficient of variation of the rows and columns of the second wafer image matrix row by row and column by column to obtain the second variation curve specifically includes:

[0019] The pixel value x of each row or column in the second wafer image matrix j Enter into formula Obtain the second standard deviation σ2 of each row or column of the second wafer image matrix, obtain the second coefficient of variation corresponding to each row or column according to the second standard deviation σ2 and the second average value μ2, and obtain the second variation curve based on all the obtained second coefficients of variation, wherein N is the number of elements in each row or column in the second wafer image matrix, and the second average value μ2 is obtained according to the pixel value of each row or column in the second wafer image matrix.

[0020] Further, determining the authenticity of the chip to be inspected based on the first variation curve and the second variation curve specifically includes:

[0021] According to the Laida criterion, the portion with a larger distance between the first variation curve and the second variation curve is eliminated;

[0022] Calculating the Pearson correlation coefficient between the remaining part of the first variation curve and the remaining part of the second variation curve to obtain the similarity between the first variation curve and the second variation curve;

[0023] When the similarity value is greater than a preset threshold, the chip to be tested is true, otherwise, the chip to be tested is false.

[0024] Furthermore, the removing of a portion having a larger distance between the first variation curve and the second variation curve according to the Laida criterion specifically includes:

[0025] According to the distance d between the corresponding points of the first variation curve and the second variation curve i , distance standard deviation and distance average, to obtain the part of the distance between corresponding points in the first variation curve and the second variation curve that is greater than a preset distance, wherein the distance standard deviation is the standard deviation of the distance between all corresponding points in the first variation curve and the second variation curve, and the distance average is the average of the distance between all corresponding points in the first variation curve and the second variation curve.

[0026] Furthermore, the method further comprises:

[0027] The sample chip and the chip to be tested are photographed respectively by using a metallographic microscope to obtain the first wafer image and the second wafer image.

[0028] Another technical solution of the present invention to solve the above technical problems is as follows:

[0029] A device for identifying the authenticity of an integrated circuit chip based on a wafer image, comprising:

[0030] An acquisition module, used for acquiring a first wafer image of a sample chip and a second wafer image of a chip to be tested;

[0031] a calculation module, configured to obtain a first variation curve according to the first wafer image, and obtain a second variation curve according to the second wafer image;

[0032] The authentication module is used to determine the authenticity of the chip to be tested based on the first variation curve and the second variation curve.

[0033] Furthermore, the calculation module is specifically used to perform filtering, smoothing and scaling processing on the first wafer image to obtain a first wafer image matrix;

[0034] Performing filtering, smoothing and scaling processing on the second wafer image to obtain a second wafer image matrix, wherein the first wafer image matrix and the second wafer image matrix have the same matrix size;

[0035] Calculating the coefficient of variation of rows and columns of the first wafer image matrix row by row and column by column to obtain the first variation curve;

[0036] The coefficient of variation of the rows and columns of the second wafer image matrix is ​​calculated row by row and column by column to obtain the second variation curve, wherein the first variation curve and the second variation curve have the same length, and the order of corresponding points on the first variation curve and the second variation curve is also the same.

[0037] In addition, the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method for identifying the authenticity of an integrated circuit chip based on wafer images as described in any one of the above technical solutions.

[0038] The present invention also provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the steps of the method for identifying the authenticity of an integrated circuit chip based on wafer images as described in any one of the above technical solutions are implemented.

[0039] Advantages of additional aspects of the present invention will be given in part in the following description, and in part will be obvious from the following description, or will be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments of the present invention or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0041] Figure 1 A schematic flow chart of a method for identifying the authenticity of an integrated circuit chip based on wafer images according to the present invention;

[0042] Figure 2 The module diagram of a device for identifying the authenticity of integrated circuit chips based on wafer images according to the present invention. DETAILED DESCRIPTION

[0043] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0044] like Figure 1 The method for identifying the authenticity of an integrated circuit chip based on a wafer image according to an embodiment of the present invention comprises the following steps:

[0045] 110. Acquire a first wafer image of a sample chip and a second wafer image of a chip to be tested.

[0046] 120. Obtain a first variation curve according to the first wafer image, and obtain the second variation curve according to the second wafer image.

[0047] 130. Determine the authenticity of the chip to be tested based on the first variation curve and the second variation curve.

[0048] Furthermore, step 120 specifically includes:

[0049] 121. Perform filtering, smoothing and scaling processing on the first wafer image to obtain a first wafer image matrix.

[0050] 122. Perform filtering, smoothing and scaling processing on the second wafer image to obtain a second wafer image matrix, wherein the matrix sizes of the first wafer image matrix and the second wafer image matrix are the same.

[0051] 123. Calculate the coefficient of variation of rows and columns of the first wafer image matrix row by row and column by column to obtain the first variation curve.

[0052] 124. Calculate the coefficient of variation of rows and columns of the second wafer image matrix row by row and column by column to obtain the second variation curve, wherein the first variation curve and the second variation curve have the same length, and the order of corresponding points on the first variation curve and the second variation curve is also the same.

[0053] Furthermore, step 123 specifically includes:

[0054] The pixel value x of each row or column in the first wafer image matrix i Enter into formula Obtaining a first standard deviation σ1 of each row or column of the first wafer image matrix, obtaining a first coefficient of variation corresponding to each row or column according to the first standard deviation σ1 and a first average value μ1, and obtaining the first variation curve based on all the obtained first coefficients of variation, wherein N is the number of elements in each row or column of the first wafer image matrix, and obtaining the first average value μ1 according to the pixel value of each row or column in the first wafer image matrix;

[0055] Step 124 specifically includes:

[0056] The pixel value x of each row or column in the second wafer image matrix j Enter into formula Obtain the second standard deviation σ2 of each row or column of the second wafer image matrix, obtain the second coefficient of variation corresponding to each row or column according to the second standard deviation σ2 and the second average value μ2, and obtain the second variation curve based on all the obtained second coefficients of variation, wherein N is the number of elements in each row or column in the second wafer image matrix, and the second average value μ2 is obtained according to the pixel value of each row or column in the second wafer image matrix.

[0057] Furthermore, step 130 specifically includes:

[0058] 131. Eliminate a portion having a larger distance between the first variation curve and the second variation curve according to the Laida criterion.

[0059] 132. Calculate the Pearson correlation coefficient between the remaining part of the first variation curve and the remaining part of the second variation curve to obtain the similarity between the first variation curve and the second variation curve.

[0060] 133. When the similarity value is greater than a preset threshold, the chip to be tested is true; otherwise, the chip to be tested is false.

[0061] Furthermore, 131 specifically includes:

[0062] According to the distance d between the corresponding points of the first variation curve and the second variation curve i , distance standard deviation and distance average, to obtain the part of the distance between corresponding points in the first variation curve and the second variation curve that is greater than a preset distance, wherein the distance standard deviation is the standard deviation of the distance between all corresponding points in the first variation curve and the second variation curve, and the distance average is the average of the distance between all corresponding points in the first variation curve and the second variation curve.

[0063] Furthermore, the sample chip and the chip to be tested are photographed respectively using a metallographic microscope to obtain the first wafer image and the second wafer image.

[0064] A method for identifying the authenticity of an integrated circuit chip based on a wafer image proposed based on the above embodiment includes obtaining a first wafer image of a sample chip and a second wafer image of a chip to be tested; obtaining a first variation curve based on the first wafer image, and obtaining a second variation curve based on the second wafer image; and determining the authenticity of the chip to be tested based on the first variation curve and the second variation curve. The present invention minimizes the influence of artificial noise in wafer images and improves the recognition rate of chip authenticity.

[0065] like Figure 2 As shown, a device for identifying the authenticity of integrated circuit chips based on wafer images includes:

[0066] The acquisition module is used to obtain a first wafer image of the sample chip and a second wafer image of the chip to be tested.

[0067] A calculation module is used to obtain a first variation curve according to the first wafer image, and to obtain the second variation curve according to the second wafer image.

[0068] The authentication module is used to determine the authenticity of the chip to be tested based on the first variation curve and the second variation curve.

[0069] Furthermore, the calculation module is specifically used to perform filtering, smoothing and scaling processing on the first wafer image to obtain a first wafer image matrix.

[0070] The second wafer image is subjected to filtering, smoothing and scaling processing to obtain a second wafer image matrix, wherein the matrix sizes of the first wafer image matrix and the second wafer image matrix are the same.

[0071] The coefficients of variation of the rows and columns of the first wafer image matrix are calculated row by row and column by column to obtain the first variation curve.

[0072] The coefficient of variation of the rows and columns of the second wafer image matrix is ​​calculated row by row and column by column to obtain the second variation curve, wherein the first variation curve and the second variation curve have the same length, and the order of corresponding points on the first variation curve and the second variation curve is also the same.

[0073] In addition, the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method for identifying the authenticity of an integrated circuit chip based on wafer images as described in any one of the above technical solutions.

[0074] The present invention also provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the steps of the method for identifying the authenticity of an integrated circuit chip based on wafer images as described in any one of the above technical solutions are implemented.

[0075] 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.

[0076] Those skilled 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 the present invention.

[0077] In the embodiments provided by the present invention, it should be understood that the disclosed devices / terminal equipment and methods can be implemented in other ways. For example, the device / terminal equipment embodiments described above are only 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.

[0078] 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.

[0079] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0080] If the integrated module / 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.

[0081] Based on such understanding, the present invention implements all or part of the processes in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by the processor, the steps of each of the above-mentioned method embodiments can be implemented. 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 may include: any entity or device capable of carrying the computer program code, recording medium, U disk, mobile hard disk, disk, optical disk, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), electric carrier signal, telecommunication signal and software distribution medium. It should be noted that the content contained in the computer-readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable media do not include electric carrier signals and telecommunication signals.

[0082] The embodiments described above are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those 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 invention, and should all be included in the protection scope of the present invention.

[0083] The above are only specific embodiments of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can easily think of various equivalent modifications or replacements within the technical scope disclosed by the present invention, and these modifications or replacements should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention shall be based on the protection scope of the claims.

Claims

1. A method for identifying the authenticity of integrated circuit chips based on wafer images, characterized in that: include: Acquire a first wafer image of a sample chip and a second wafer image of a chip to be tested; Obtain a first variation curve according to the first wafer image, and obtain the second variation curve according to the second wafer image; obtain a coefficient of variation corresponding to each row or column according to the standard deviation and the average value of each row or column of the wafer image matrix, and obtain a variation curve based on the obtained coefficient of variation; The authenticity of the chip to be tested is determined based on the first variation curve and the second variation curve, specifically by eliminating a portion with a larger distance between the first variation curve and the second variation curve and then calculating the similarity between the two.

2. The method for identifying the authenticity of integrated circuit chips based on wafer images according to claim 1, characterized in that: The obtaining of a first variation curve according to the first wafer image and the obtaining of a second variation curve according to the second wafer image specifically include: Performing filtering, smoothing and scaling processing on the first wafer image to obtain a first wafer image matrix; Performing filtering, smoothing and scaling processing on the second wafer image to obtain a second wafer image matrix, wherein the first wafer image matrix and the second wafer image matrix have the same matrix size; Calculating the coefficients of variation of rows and columns of the first wafer image matrix row by row and column by column to obtain the first variation curve; The coefficient of variation of the rows and columns of the second wafer image matrix is ​​calculated row by row and column by column to obtain the second variation curve, wherein the first variation curve and the second variation curve have the same length, and the order of corresponding points on the first variation curve and the second variation curve is also the same.

3. The method for identifying the authenticity of integrated circuit chips based on wafer images according to claim 2, characterized in that: Calculating the coefficient of variation of the rows and columns of the first wafer image matrix row by row and column by column to obtain the first variation curve specifically includes: The pixel value of each row or column in the first wafer image matrix Enter into formula , obtain the first standard deviation of each row or column of the first wafer image matrix , according to the first standard deviation and the first average , obtain the first coefficient of variation corresponding to each row or column, and obtain the first variation curve based on all the first coefficients of variation obtained, wherein N is the number of elements in each row or column in the first wafer image matrix, and the first average value is obtained according to the pixel value of each row or column in the first wafer image matrix. ; Calculating the coefficient of variation of the rows and columns of the second wafer image matrix row by row and column by column to obtain the second variation curve specifically includes: The pixel value of each row or column in the second wafer image matrix Enter into formula , obtain the second standard deviation of each row or column of the second wafer image matrix , according to the second standard deviation and the second mean , obtain the second coefficient of variation corresponding to each row or column, and obtain the second variation curve based on all the obtained second coefficients of variation, wherein N is the number of elements in each row or column in the second wafer image matrix, and the second average value is obtained according to the pixel value of each row or column in the second wafer image matrix. .

4. The method for identifying the authenticity of integrated circuit chips based on wafer images according to claim 2, characterized in that: The determining the authenticity of the chip to be inspected based on the first variation curve and the second variation curve specifically includes: According to the Laida criterion, the portion with a larger distance between the first variation curve and the second variation curve is eliminated; Calculating the Pearson correlation coefficient between the remaining part of the first variation curve and the remaining part of the second variation curve to obtain the similarity between the first variation curve and the second variation curve; When the similarity value is greater than a preset threshold, the chip to be tested is true, otherwise, the chip to be tested is false.

5. The method for identifying the authenticity of integrated circuit chips based on wafer images according to claim 4, characterized in that: The removing a portion with a larger distance between the first variation curve and the second variation curve according to the Laida criterion specifically includes: According to the distance between the corresponding points of the first variation curve and the second variation curve d i , distance standard deviation and distance average, to obtain the part of the distance between corresponding points in the first variation curve and the second variation curve that is greater than a preset distance, wherein the distance standard deviation is the standard deviation of the distance between all corresponding points in the first variation curve and the second variation curve, and the distance average is the average of the distance between all corresponding points in the first variation curve and the second variation curve.

6. The method for identifying the authenticity of an integrated circuit chip based on wafer images according to any one of claims 1 to 5, characterized in that: The method further comprises: The sample chip and the chip to be tested are photographed respectively by using a metallographic microscope to obtain the first wafer image and the second wafer image.

7. A device for identifying the authenticity of integrated circuit chips based on wafer images, characterized in that: include: An acquisition module, used for acquiring a first wafer image of a sample chip and a second wafer image of a chip to be tested; A calculation module, configured to obtain a first variation curve according to the first wafer image, and obtain a second variation curve according to the second wafer image; obtain a coefficient of variation corresponding to each row or column according to a standard deviation and an average value of each row or column of a wafer image matrix, and obtain a variation curve based on the obtained coefficient of variation; The authentication module is used to determine the authenticity of the chip to be tested based on the first variation curve and the second variation curve, specifically by calculating the similarity between the first variation curve and the second variation curve after removing the part with a larger distance between the two.

8. The device for identifying the authenticity of integrated circuit chips based on wafer images according to claim 7, characterized in that: The calculation module is specifically used to perform filtering, smoothing and scaling processing on the first wafer image to obtain a first wafer image matrix; Performing filtering, smoothing and scaling processing on the second wafer image to obtain a second wafer image matrix, wherein the first wafer image matrix and the second wafer image matrix have the same matrix size; Calculating the coefficients of variation of rows and columns of the first wafer image matrix row by row and column by column to obtain the first variation curve; The coefficient of variation of the rows and columns of the second wafer image matrix is ​​calculated row by row and column by column to obtain the second variation curve, wherein the first variation curve and the second variation curve have the same length, and the order of corresponding points on the first variation curve and the second variation curve is also the same.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the steps of the method for identifying the authenticity of an integrated circuit chip based on a wafer image as described in any one of claims 1 to 6 are implemented.

10. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, the steps of the method for identifying the authenticity of an integrated circuit chip based on a wafer image as described in any one of claims 1 to 6 are implemented.

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