Semiconductor chip detection method

Abstract

The present application provides a method for detecting a semiconductor chip, wherein the surface of the semiconductor chip has a plurality of cathode comb bars, and the method comprises: obtaining image data of the surface structure of the semiconductor chip; using image processing technology to analyze the image data to identify the position of each cathode comb bar and obtain the position information corresponding to each cathode comb bar; and according to each position information, controlling the movement of the probe so that the probe contacts each cathode comb bar in turn to detect whether each cathode comb bar has a defect. The present application solves the problem that in the existing semiconductor chip detection process, due to the error between the actual position of the cathode comb bar and the preset position, the test of the cathode comb bar in the chip is mainly manually calibrated, resulting in low test efficiency and low accuracy.

Description

Technical Field

[0001] The present application relates to the field of semiconductor technology, and in particular to a method for detecting a semiconductor chip. Background Art

[0002] Many semiconductor chips are composed of multi-cell structures connected in parallel. If there is a defect in one of the cells, it will affect the normal operation of the entire chip.

[0003] Taking the GCT (Gate-Commutated Thyristor) chip as an example, the GCT (gate-commutated thyristor) chip is composed of thousands of small GCT cells, which share anodes, while the cathodes and gates are connected in parallel. Usually, a rectangular comb-shaped cathode unit is arranged radially in concentric rings. This design can effectively disperse the current during the switching process and avoid excessive current concentration. Since GCT is a whole-wafer device, once a comb has a defect, it will not only affect the function of the comb, but may also cause local burning of the chip and cause the entire chip to fail, seriously reducing the yield and reliability of the product. Therefore, it is necessary to use a probe to test the cathode comb in the GCT chip. However, since the GCT chip cells actually produced are arranged in a ring, but not strictly centrally symmetrical, it is difficult to match the chip with the design drawing, and there is a deviation between the actual chip cell arrangement and the design drawing. Therefore, the test of the cathode comb in the GCT chip is mainly done manually to calibrate the probe. The test efficiency is low and the accuracy is also low. Summary of the invention

[0004] The main purpose of the present application is to provide a semiconductor chip detection method to solve the problem that in the existing semiconductor chip detection process, due to the error between the actual position of the cathode comb bar and the preset position, the test of the cathode comb bar in the chip is mainly calibrated manually, resulting in low test efficiency and low accuracy.

[0005] In order to achieve the above-mentioned purpose, according to one aspect of the present application, a method for detecting a semiconductor chip is provided, wherein the surface of the semiconductor chip has multiple cathode comb bars, and the method comprises: acquiring image data of the surface structure of the semiconductor chip; using image processing technology to analyze the image data to identify the position of each cathode comb bar and obtain the position information corresponding to each cathode comb bar; according to each position information, controlling the movement of the probe so that the probe contacts each cathode comb bar in turn to detect whether each cathode comb bar has defects.

[0006] Optionally, the image data is analyzed using image processing technology to identify the position of each cathode comb bar and obtain the position information corresponding to each cathode comb bar, including: preprocessing the image data, the preprocessing including denoising, grayscale and binarization; analyzing the preprocessed image data to obtain the contour information of each cathode comb bar; and obtaining each position information at least based on each contour information.

[0007] Optionally, the preprocessed image data is analyzed to obtain contour information of each cathode comb bar, including: using an edge detection algorithm to perform edge detection on the preprocessed image data to obtain edge information of each cathode comb bar; based on each edge information, using a contour extraction algorithm to determine each contour information.

[0008] Optionally, edge detection is performed on the preprocessed image data using an edge detection algorithm, including: edge detection is performed on the preprocessed image data using a Canny algorithm.

[0009] Optionally, determining each piece of contour information by using a contour extraction algorithm according to each piece of edge information includes: determining each piece of contour information by using a findContours algorithm according to each piece of edge information.

[0010] Optionally, at least based on each of the contour information, each of the position information is obtained, including: using a preset contour template to perform contour matching on each of the contour information to obtain each of the position information, wherein the contour template represents a preset ideal contour of the cathode comb bar.

[0011] Optionally, a preset contour template is used to perform contour matching on each of the contour information to obtain each of the position information, including: using a preset contour template to perform contour matching on each of the contour information to obtain a contour matching result; based on the contour matching result, the center coordinates of each of the cathode comb bars are determined to obtain each of the position information.

[0012] Optionally, acquiring the image data of the surface structure of the semiconductor chip includes: photographing the surface structure of the semiconductor chip using a camera to obtain the image data.

[0013] Optionally, after controlling the movement of the probe according to each of the position information so that the probe contacts each of the cathode comb bars in turn to detect whether each of the cathode comb bars has defects, the method further includes: removing the cathode comb bars with defects.

[0014] By applying the technical solution of the present application, the image data of the surface structure of the semiconductor chip is first obtained, and then the image processing technology is used to analyze the image data to identify the position of each cathode comb bar and obtain the position information corresponding to each cathode comb bar. Finally, according to each position information, the probe is controlled to move so that the probe contacts each cathode comb bar in turn to detect whether each cathode comb bar has defects. Compared with the existing semiconductor chip detection process, due to the error between the actual position of the cathode comb bar and the preset position, the test of the cathode comb bar in the chip is mainly done manually to calibrate the probe, resulting in low test efficiency and low accuracy, the present application obtains the image data of the chip surface structure, identifies the position information of the cathode comb bar by processing the image data, controls the probe to move according to the acquired position information, makes the probe contact the cathode comb bar in turn, detects whether the cathode comb bar has defects, realizes automated detection, avoids the subjectivity and inconsistency of manual detection, and improves detection efficiency and accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] The drawings constituting part of the present application are used to provide a further understanding of the present application. The exemplary embodiments and descriptions of the present application are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0016] Figure 1 A hardware structure block diagram of a mobile terminal for executing a semiconductor chip detection method provided in an embodiment of the present application is shown;

[0017] Figure 2 A schematic flow chart of a semiconductor chip detection method provided according to an embodiment of the present application is shown.

[0018] The above drawings include the following reference numerals:

[0019] 102, processor; 104, memory; 106, transmission device; 108, input and output devices. DETAILED DESCRIPTION

[0020] It should be noted that, in the absence of conflict, the embodiments and features in the embodiments of the present application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0021] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present application.

[0022] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequential order. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present application described here. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0023] As introduced in the background technology, in the existing semiconductor chip detection process, due to the error between the actual position of the cathode comb bar and the preset position, the test of the cathode comb bar in the chip is mainly calibrated manually, resulting in low test efficiency and low accuracy. To solve the above problems, an embodiment of the present application provides a semiconductor chip detection method.

[0024] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the accompanying drawings in the embodiments of the present invention.

[0025] The method embodiments provided in the embodiments of the present application can be executed in a mobile terminal, a computer terminal or a similar computing device. Taking running on a mobile terminal as an example, Figure 1 FIG. 1 is a hardware structure block diagram of a mobile terminal for a semiconductor chip detection method according to an embodiment of the present invention. Figure 1 As shown, the mobile terminal may include one or more ( Figure 1 Only one is shown in the figure) a processor 102 (the processor 102 may include but is not limited to a processing device such as a microprocessor MCU or a programmable logic device FPGA) and a memory 104 for storing data, wherein the mobile terminal may also include a transmission device 106 and an input / output device 108 for communication functions. It can be understood by those skilled in the art that Figure 1 The structure shown is only for illustration and does not limit the structure of the mobile terminal. Figure 1 More or fewer components as shown, or with Figure 1 Different configurations are shown.

[0026] The memory 104 can be used to store computer programs, for example, software programs and modules of application software, such as the computer program corresponding to the detection method of the semiconductor chip in the embodiment of the present invention. The processor 102 executes various functional applications and data processing by running the computer program stored in the memory 104, that is, the above method is implemented. The memory 104 may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory 104 may further include a memory remotely arranged relative to the processor 102, and these remote memories can be connected to the mobile terminal via a network. Examples of the above-mentioned network include but are not limited to the Internet, an intranet, a local area network, a mobile communication network, and a combination thereof. The transmission device 106 is used to receive or send data via a network. The above-mentioned specific examples of the network may include a wireless network provided by a communication provider of the mobile terminal. In one example, the transmission device 106 includes a network adapter (Network Interface Controller, referred to as NIC), which can be connected to other network devices through a base station so as to communicate with the Internet. In one example, the transmission device 106 may be a radio frequency (RF) module, which is used to communicate with the Internet wirelessly.

[0027] In this embodiment, a method for detecting a semiconductor chip running on a mobile terminal, a computer terminal or a similar computing device is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0028] Figure 2 is a flow chart of a method for detecting a semiconductor chip according to an embodiment of the present application. The surface of the semiconductor chip has a plurality of cathode comb strips, such as Figure 2 As shown, the method comprises the following steps:

[0029] Step S201, acquiring image data of the surface structure of the semiconductor chip;

[0030] Step S202, using image processing technology to analyze the image data to identify the position of each of the cathode comb bars, and obtain the position information corresponding to each of the cathode comb bars;

[0031] Step S203, according to each of the above position information, control the movement of the probe so that the probe contacts each of the above cathode comb bars in turn to detect whether each of the above cathode comb bars has defects.

[0032] Through this embodiment, the image data of the surface structure of the semiconductor chip is first obtained, and then the image processing technology is used to analyze the image data to identify the position of each cathode comb bar, and obtain the position information corresponding to each cathode comb bar. Finally, according to each position information, the probe is controlled to move so that the probe contacts each cathode comb bar in turn to detect whether each cathode comb bar has defects. Compared with the existing semiconductor chip detection process, due to the error between the actual position of the cathode comb bar and the preset position, the test of the cathode comb bar in the chip is mainly manually calibrated, resulting in low test efficiency and low accuracy. In this application, the image data of the chip surface structure is obtained, and the position information of the cathode comb bar is identified by processing the image data. According to the acquired position information, the probe is controlled to move so that the probe contacts the cathode comb bar in turn to detect whether the cathode comb bar has defects, thereby realizing automatic detection, avoiding the subjectivity and inconsistency of manual detection, and improving detection efficiency and accuracy.

[0033] In addition, automated testing reduces reliance on manual labor and reduces the labor cost of testing. At the same time, high-precision testing can reduce the scrap rate of chips, reduce the waste of raw materials, and further save costs.

[0034] In an optional solution, the image data is analyzed using image processing technology to identify the position of each of the cathode comb bars and obtain the position information corresponding to each of the cathode comb bars, including: preprocessing the image data, the preprocessing including denoising, grayscale and binarization; analyzing the preprocessed image data to obtain the contour information of each of the cathode comb bars; and obtaining the position information at least based on the contour information. In this embodiment, the preprocessing steps, including denoising, grayscale and binarization, can effectively improve the quality of the image data, remove interference information in the image, improve the accuracy and reliability of subsequent image analysis, and further ensure that the position information of the cathode comb bars obtained subsequently is relatively accurate.

[0035] According to some exemplary embodiments of the present application, the preprocessed image data is analyzed to obtain the contour information of each of the cathode comb strips, including: using an edge detection algorithm to perform edge detection on the preprocessed image data to obtain edge information of each of the cathode comb strips; and using a contour extraction algorithm to determine each of the above-mentioned contour information based on each of the above-mentioned edge information. In this embodiment, the combination of edge detection and contour extraction can accurately identify and locate the cathode comb strips in the image, providing a basis for the precise contact of the probe, and improving the accuracy and reliability of the detection. In addition, edge detection and contour extraction are both fast image processing steps that can be completed in a very short time, which makes the entire detection process more efficient, reduces detection time, and speeds up the production process.

[0036] In other embodiments, edge detection is performed on the preprocessed image data using an edge detection algorithm, including: performing edge detection on the preprocessed image data using a Canny algorithm. In this embodiment, the Canny algorithm can effectively identify the real edges in the image, reduce the interference of pseudo edges, and further improve the accuracy of detection.

[0037] Specifically, other edge detection algorithms may also be used to perform edge detection on image data, such as Sobel operator, Prewitt operator, Roberts operator, and Laplacian operator, etc., and this application does not impose any specific limitation on this.

[0038] According to other exemplary embodiments of the present application, based on each of the above edge information, a contour extraction algorithm is used to determine each of the above contour information, including: based on each of the above edge information, a findContours algorithm is used to determine each of the above contour information. In this embodiment, the findContours algorithm can accurately determine the contour information of the object in the image based on the edge information obtained by edge detection, providing accurate data support for the subsequent cathode comb position identification.

[0039] In some other optional schemes of the present application, at least based on each of the above-mentioned contour information, each of the above-mentioned position information is obtained, including: using a preset contour template to perform contour matching on each of the above-mentioned contour information to obtain each of the above-mentioned position information, wherein the above-mentioned contour template represents the preset ideal contour of the above-mentioned cathode comb bar. In this embodiment, the contour matching technology can quickly locate the cathode comb bar according to the template, reduce the probe positioning time, and further improve the detection efficiency.

[0040] In some other optional schemes of the present application, using a preset contour template, contour matching is performed on each of the above contour information to obtain each of the above position information, including: using a preset contour template, contour matching is performed on each of the above contour information to obtain a contour matching result; according to the contour matching result, the center coordinates of each of the above cathode comb bars are determined to obtain each of the above position information. In this embodiment, by determining the center coordinates through the contour matching result, precise contact with the cathode comb bar can be achieved, further improving the accuracy and reliability of the detection.

[0041] Specifically, the extracted contour information is matched with the preset cathode comb bar template (i.e., the contour template) to find the best matching contour, which is the actual position of the cathode comb bar. Based on the matched contour, the center coordinates or other reference coordinates of the cathode comb bar are obtained, and the position coordinates of each cathode comb bar are recorded.

[0042] Specifically, the specific steps for contour matching are as follows: Contour template creation: In the design stage, a mathematical model of the contour of the cathode comb strip is created based on the design drawings of the cathode comb strip. This usually involves extracting the key features of the cathode comb strip, such as width, spacing, direction, etc., and using these features to build a contour template. The contour template can be based on a point set, an edge, or even a feature point (such as a corner point); Contour extraction: In the image processing stage, the contour of the cathode comb strip needs to be extracted from the captured chip image first. This is usually achieved through an edge detection algorithm (such as Canny edge detection), which can detect edges in an image and output the pixel position of the edge. Then, a contour extraction algorithm (such as OpenCV (Open Source Computer Vision) Library, an open source computer vision library) to further process these edge pixels to form a continuous contour; Template matching: Match the extracted cathode comb contour with the preset contour template, which can be achieved in a variety of ways, such as: Shape matching: Calculate the shape similarity between the extracted contour and the contour template. Common methods include using the contour's Fourier descriptor or shape context to describe the contour features, and then compare the similarity of these features; Position matching: If the position of the contour template is known, the contour template can be projected into the coordinate system of the current image, and then the position difference between the template and the extracted contour is calculated to find the best matching position; Feature matching: For more complex matching, feature matching algorithms such as SIFT (Scale-Invariant Feature Transform), SURF (Speeded-Up RobustFeatures) or ORB (Oriented FAST and Rotated BRIEF, directional acceleration segment and rotation binary robust independent feature)), these algorithms can detect and describe feature points, and then find matching feature points between the template and the extracted contour to determine the relative position of the contour; optimal matching selection: when performing contour matching, multiple potential matching results may be obtained, and it is necessary to use certain criteria (such as matching score, position deviation, shape similarity, etc.) to select the best matching result, that is, the cathode comb contour closest to the preset template; coordinate transformation and correction: once the best matching contour is determined, its position needs to be converted to the position in the actual coordinate system of the chip to obtain the position information, which involves coordinate transformation and translation correction to ensure that the probe can accurately locate the cathode comb on the chip.

[0043] Specifically, the position information in the image coordinate system is converted into the position in the actual coordinate system of the chip (the photographed coordinates are matched with the actual chip coordinates), that is, the mapping relationship between the image coordinate system and the physical coordinate system is established, which usually includes the following steps: 1) Select reference points: Select one or more reference points with known positions on the chip surface. These reference points are clear in the chip design drawings or CAD models, such as specific marking points. The selection of reference points should take into account their clarity and stability in the image to ensure accurate matching; 2) Image reference point identification: Use image processing techniques such as pattern matching, feature detection (such as SIFT, SURF or ORB), edge detection and other methods to identify the above-selected reference points from the image data; 3) Calculate the mapping relationship: Once the reference points are identified in the image, the mapping relationship can be calculated through the coordinates of these points in the image coordinate system and the physical coordinate system. A common method is to use perspective transformation (Homography) or similarity transformation (Affine Transformation), which requires at least four corresponding points (for perspective transformation) or three corresponding points (for similarity transformation). Through these points, image processing libraries such as OpenCV provide functions (such as findHomography or getAffineTransform) to calculate the transformation matrix; 4) Apply the mapping relationship: Use the calculated transformation matrix to transform the coordinates in the image to the physical coordinate system, so that the position of the cathode comb in the actual chip arrangement can be obtained. Usually, this process is to identify the contour of the cathode comb and then transform the center point or other feature points of the contour; 5) Error correction: In actual application In use, due to the distortion of the camera, changes in shooting angles, etc., the coordinate transformation may produce certain errors. Therefore, the transformation results need to be corrected. This can be achieved by calibrating several known points in the physical coordinate system and then adjusting the transformation matrix according to the calibration results; 6) Establish a coordinate system: determine an origin and coordinate axis direction as a reference, which is usually based on the fixed features of the chip, such as a corner or center of the chip. In this way, all points on the chip, including the cathode comb bar, can be represented as a set of coordinate values ​​relative to the origin; 7) Control the movement of the probe: Use the position coordinates of the cathode comb bar in the physical coordinate system to control the probe to move to the corresponding position to detect the cathode comb bar. Through the above steps, accurate mapping from the photographed coordinates to the actual chip coordinates can be achieved, thereby guiding the subsequent automated detection process.

[0044] According to some other exemplary embodiments of the present application, obtaining the image data of the surface structure of the semiconductor chip includes: using a camera to photograph the surface structure of the semiconductor chip to obtain the image data. In this embodiment, a high-resolution camera is used for image acquisition, which can capture the tiny details of the cathode comb strips and provide high-quality raw data for subsequent image processing.

[0045] Specifically, an industrial camera (such as a machine vision camera) may be used to photograph the surface structure of the semiconductor chip, or a microscope camera may be used to photograph it, and this application does not impose any specific restrictions on this.

[0046] According to some further exemplary embodiments of the present application, after controlling the probe to move according to each of the above position information so that the probe contacts each of the above cathode comb bars in turn to detect whether each of the above cathode comb bars has defects, the method further includes: removing the above cathode comb bars with defects. In this embodiment, by removing the defective cathode comb bars, it is possible to effectively prevent unqualified products from flowing into subsequent production links, thereby improving the yield rate of semiconductor chips.

[0047] Specifically, modern path planning techniques (such as RRT or deep reinforcement learning) can be used to calculate the optimal path for the probe movement in real time based on the actual position information of the chip cathode comb bars. This can avoid ineffective movement of the probe during the detection process and reduce the detection time, while ensuring precise contact between the probe and each cathode comb bar.

[0048] Specifically, a system consisting of two or more cameras can be used to simultaneously photograph semiconductor chips from different angles. In addition, after obtaining the actual position information of the cathode comb, before controlling the movement of the probe, a high-precision positioning system (such as laser positioning, optical positioning, etc.) can be used for secondary verification to ensure that the final position of the probe is consistent with the expected position, thereby further avoiding inaccurate detection caused by positioning errors.

[0049] In order to enable those skilled in the art to more clearly understand the technical solution of the present application, the implementation process of the semiconductor chip detection method of the present application will be described in detail below in combination with specific embodiments.

[0050] This embodiment relates to a specific method for detecting a semiconductor chip. The surface of the semiconductor chip has a plurality of cathode comb strips. The method comprises the following steps:

[0051] Step S1: Acquire image data of the surface structure of a semiconductor chip;

[0052] Step S2: preprocessing the image data, including denoising, grayscale conversion and binarization;

[0053] Step S3: using an edge detection algorithm to perform edge detection on the preprocessed image data to obtain edge information of each cathode comb bar;

[0054] Step S4: Determine each contour information by using a contour extraction algorithm according to each edge information;

[0055] Step S5: using a preset contour template to perform contour matching on each contour information to obtain each position information, wherein the contour template represents the preset ideal contour of the cathode comb bar;

[0056] Step S6: According to each position information, control the probe to move so that the probe contacts each cathode comb bar in turn to detect whether each cathode comb bar has defects;

[0057] Step S7: removing the cathode comb bars with defects.

[0058] It should be noted that the steps shown in the flowcharts of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and that, although a logical order is shown in the flowcharts, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0059] Obviously, those skilled in the art should understand that the above modules or steps of the present invention can be implemented by a general computing device, they can be concentrated on a single computing device, or distributed on a network composed of multiple computing devices, they can be implemented by a program code executable by a computing device, so that they can be stored in a storage device and executed by the computing device, and in some cases, the steps shown or described can be executed in a different order than here, or they can be made into individual integrated circuit modules, or multiple modules or steps therein can be made into a single integrated circuit module for implementation. Thus, the present invention is not limited to any specific combination of hardware and software.

[0060] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0061] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0062] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0063] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0064] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0065] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0066] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0067] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0068] From the above description, it can be seen that the above embodiments of the present application achieve the following technical effects:

[0069] In the semiconductor chip detection method of the present application, the image data of the surface structure of the semiconductor chip is first obtained, and then the image processing technology is used to analyze the image data to identify the position of each cathode comb bar, and the position information corresponding to each cathode comb bar is obtained. Finally, according to each position information, the probe is controlled to move so that the probe contacts with each cathode comb bar in turn to detect whether each cathode comb bar has defects. Compared with the existing semiconductor chip detection process, due to the error between the actual position of the cathode comb bar and the preset position, the test of the cathode comb bar in the chip is mainly manually calibrated, resulting in low test efficiency and low accuracy. In the present application, the image data of the chip surface structure is obtained, the position information of the cathode comb bar is identified by processing the image data, and the probe is controlled to move according to the acquired position information so that the probe contacts with the cathode comb bar in turn to detect whether the cathode comb bar has defects, thereby realizing automatic detection, avoiding the subjectivity and inconsistency of manual detection, and improving detection efficiency and accuracy.

[0070] The above description is only the preferred embodiment of the present application and is not intended to limit the present application. For those skilled in the art, the present application may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A method for detecting a semiconductor chip, characterized in that: The surface of the semiconductor chip has a plurality of cathode comb strips, and the method comprises: Acquiring image data of the surface structure of the semiconductor chip; Analyzing the image data by using image processing technology to identify the position of each cathode comb bar and obtain the position information corresponding to each cathode comb bar; According to each of the position information, the probe is controlled to move so that the probe contacts each of the cathode comb bars in turn to detect whether each of the cathode comb bars has defects. The image data is analyzed by using image processing technology to identify the position of each cathode comb bar and obtain the position information corresponding to each cathode comb bar, including: Preprocessing the image data, wherein the preprocessing includes denoising, grayscale conversion and binarization; Using an edge detection algorithm, edge detection is performed on the preprocessed image data to obtain edge information of each cathode comb bar; According to each of the edge information, using a contour extraction algorithm, determining the contour information of each of the cathode comb bars; Using a preset contour template, contour matching is performed on the contour information of each cathode comb bar to obtain a contour matching result, wherein the contour template represents the preset ideal contour of the cathode comb bar; According to the contour matching result, the center coordinates of each cathode comb bar are determined to obtain the position information.

2. The method for detecting a semiconductor chip according to claim 1, characterized in that: Performing edge detection on the preprocessed image data using an edge detection algorithm, including: The Canny algorithm is used to perform edge detection on the preprocessed image data.

3. The method for detecting a semiconductor chip according to claim 1, characterized in that: According to each of the edge information, using a contour extraction algorithm, determining the contour information of each of the cathode comb bars, including: According to each of the edge information, the contour information of each of the cathode comb bars is determined using the findContours algorithm.

4. The method for detecting a semiconductor chip according to claim 1, wherein: Acquiring image data of the surface structure of the semiconductor chip, comprising: The surface structure of the semiconductor chip is photographed by using a camera to obtain the image data.

5. The method for detecting a semiconductor chip according to claim 1, wherein: After controlling the probe to move according to each of the position information so that the probe contacts each of the cathode comb bars in sequence to detect whether each of the cathode comb bars has a defect, the method further includes: The cathode comb bars having defects are removed.

Images