A method and device for identifying opening of a chip

Abstract

The application belongs to the technical field of image recognition, and provides a chip opening recognition method and device, the chip opening recognition method comprises the following steps: collecting a current real-time image, and rotating the current real-time image to a preset direction to obtain a current chip image; obtaining a region of interest in a standard template image; wherein the region of interest comprises a chip die region, a wire bonding region and / or a pin region; extracting a to-be-recognized region corresponding to the region of interest in the current chip image; and controlling a chip opening process according to the region similarity between the region of interest and the to-be-recognized region corresponding to the region of interest. In the above scheme, efficient, accurate and automatic chip opening is realized, and the opening efficiency and recognition accuracy are significantly improved.

Description

Technical Field

[0001] This invention belongs to the technical field of image recognition, and particularly relates to a method and apparatus for identifying chip unpacking. Background Technology

[0002] Chip unpacking is a critical step in the manufacturing and maintenance of electronic devices. Chip unpacking is typically used for fault analysis, quality inspection, or other repair operations. However, identifying and locating chips during the unpacking process has always been a challenge. Traditional chip unpacking methods rely primarily on manual operation and visual inspection, which is not only time-consuming and labor-intensive but also struggles to guarantee accuracy and efficiency.

[0003] With the development of technology, image processing technology and machine learning algorithms have been widely applied in various fields, including the automation of chip unpacking. Image recognition technology can significantly improve the accuracy and efficiency of chip unpacking, reducing human error and operation time. However, existing automated chip unpacking and recognition methods still have some shortcomings. Existing methods often fail to accurately locate the region of interest, affecting the accuracy of subsequent recognition. Summary of the Invention

[0004] In view of this, embodiments of the present invention provide a method and apparatus for identifying chip unpacking, in order to solve the technical problem that existing methods often cannot accurately locate the region of interest.

[0005] A first aspect of this invention provides a method for identifying chip unpacking, the method comprising:

[0006] Acquire a real-time image and rotate the real-time image to a preset direction to obtain a current chip image; wherein, the preset direction refers to the direction corresponding to the standard chip area in the standard template image;

[0007] Obtain the region of interest in a standard template image; wherein the region of interest includes the die area, the wire bonding area, and / or the pin area;

[0008] Extract the region to be identified corresponding to the region of interest from the current chip image;

[0009] The chip unpacking process is controlled based on the regional similarity between the region of interest and the corresponding region to be identified.

[0010] Further, the step of acquiring the current real-time image and rotating the current real-time image to a preset direction to obtain the current chip image includes:

[0011] Acquire images of unopened chips and extract the unopened chip region from the images;

[0012] Extract the current identification graphic from the unopened chip area; wherein, the current identification graphic refers to the product identification, mark or specific pattern printed on the chip packaging area;

[0013] Extract the current orientation of the current identifier graphic;

[0014] During the chip unpacking process, a real-time image is acquired, and the real-time image is rotated to a preset direction based on the current direction to obtain the current chip image.

[0015] Further, the step of extracting the current direction of the current identifier graphic includes:

[0016] Extract the standard identifier graphics from the standard template image;

[0017] A first coordinate system is constructed with the center of the standard package area as the origin and the length and width directions as axes;

[0018] Based on the first coordinate system, multiple first sampling points on the edge of the standard logo graphic are extracted within a preset angle range at fixed horizontal coordinate intervals; wherein, the preset angle range includes 0 degrees to 90 degrees, 90 degrees to 180 degrees, 180 degrees to 270 degrees, or 270 degrees to 360 degrees.

[0019] A second coordinate system is constructed with the center of the current logo graphic as the origin and the length and width directions as axes;

[0020] Based on the second coordinate system, multiple second sampling points on the edge of the current identifier graphic are extracted at fixed horizontal coordinate intervals within multiple current angle ranges; wherein, the multiple current angle ranges include 0 degrees to 90 degrees, 90 degrees to 180 degrees, 180 degrees to 270 degrees, and 270 degrees to 360 degrees.

[0021] The current orientation of the current identifier graphic is calculated based on multiple first sampling points and multiple second sampling points.

[0022] Further, the step of calculating the current orientation of the current identifier graphic based on multiple first sampling points and multiple second sampling points includes:

[0023] Calculate the first distance between multiple first sampling points and the origin, and construct a first distance vector from the multiple first distances;

[0024] Calculate the second distance between multiple second sampling points and the origin, and construct a second distance vector from the multiple second distances;

[0025] Calculate the vector similarity between the second distance vector and the first distance vector for each of the multiple current angle ranges;

[0026] Calculate the directional angle between the current angle range and the preset angle range corresponding to the maximum vector similarity;

[0027] The included angle of the directions is taken as the current direction.

[0028] Furthermore, the step of controlling the chip unpacking process based on the regional similarity between the region of interest and the corresponding region to be identified includes:

[0029] Calculate the region similarity between the region of interest and the region to be identified corresponding to the region of interest;

[0030] If the similarity of the region is lower than the preset similarity, the chip unpacking process continues and subsequent real-time images are acquired.

[0031] When the similarity of the regions is not lower than the preset similarity, the chip unpacking process is stopped.

[0032] Further, the step of calculating the region similarity between the region of interest and the corresponding region to be identified includes:

[0033] Extract the first pixel value and the second pixel value corresponding to the same pixel position from the region of interest and the region to be identified corresponding to the region of interest;

[0034] Calculate the absolute difference between the first pixel value and the second pixel value;

[0035] If the absolute value difference is less than the first value, then the position of that pixel is taken as the position of the pixel of interest;

[0036] If the absolute value difference is not less than the first value, then the position of that pixel is taken as the position of a non-interesting pixel.

[0037] Extract the neighboring pixel positions corresponding to each pixel position of interest to obtain the current image region composed of multiple neighboring pixel positions of interest or a single pixel position of interest;

[0038] Count the number of pixel positions in the current image region;

[0039] The current image region with a number of pixel positions greater than the second number is taken as the target image region;

[0040] The similarity of the regions is calculated based on the number of pixel positions corresponding to the target image region and the absolute value difference of each pixel position.

[0041] Further, the step of calculating the region similarity based on the number of pixel positions corresponding to the target image region and the absolute value difference corresponding to each pixel position includes:

[0042] Find the maximum absolute difference;

[0043] Calculate the quality weight for each pixel location based on the maximum absolute difference and the absolute difference at each pixel location; where, quality weight = d i d represents the absolute difference at the position of the i-th pixel. max This represents the maximum absolute value difference. Indicates the attenuation coefficient;

[0044] The region contribution is calculated based on the number of pixel locations corresponding to the target image region and the quality weight corresponding to each pixel location; where, region contribution = n j w represents the number of pixel positions corresponding to the j-th target image region. i This represents the quality weight corresponding to the position of the i-th pixel.

[0045] The average value of the regional contribution corresponding to multiple target image regions is used as the region similarity.

[0046] A second aspect of the present invention provides an apparatus for identifying chip unpacking, comprising:

[0047] The acquisition unit is used to acquire the current real-time image and rotate the current real-time image to a preset direction to obtain the current chip image; wherein, the preset direction refers to the direction corresponding to the standard chip area in the standard template image;

[0048] An acquisition unit is used to acquire a region of interest in a standard template image; wherein the region of interest includes a die area, a wire bonding area, and / or a package pin area;

[0049] Extraction unit, used to extract the region to be identified corresponding to the region of interest in the current chip image;

[0050] The control unit is used to control the chip unpacking process based on the regional similarity between the region of interest and the region to be identified corresponding to the region of interest.

[0051] A third aspect of the present invention provides a terminal device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps in the method for opening the identification chip described in the first aspect.

[0052] A fourth aspect of the present invention provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps in the method for identifying chip unpacking described in the first aspect.

[0053] The beneficial effects of this invention compared to existing technologies are as follows: By rotating the current real-time image to a preset direction, the image orientation is ensured to be consistent for each processing operation. Since chip images may exhibit different features in different directions, a unified image orientation helps extract and match image features, improving the accuracy and consistency of recognition. Using a standard template image as a reference ensures a reliable benchmark throughout the recognition process, thereby reducing errors caused by differences in image orientation and angle. By acquiring the region of interest (such as the chip die area, wire bonding area, and pin area) in the standard template image and extracting the corresponding region to be identified in the current chip image, the key parts of the chip can be accurately located. This process avoids recognition errors caused by inaccurate region extraction in traditional methods. Judgment is made based on the similarity between the region of interest and the corresponding region to be identified, further improving recognition accuracy. Similarity calculation can effectively distinguish subtle differences, thus ensuring the reliability of the recognition results. In summary, this invention achieves high efficiency, accuracy, and automation in the chip unpacking process, significantly improving unpacking efficiency and recognition accuracy. Attached Figure Description

[0054] To more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings used in the description of the embodiments or related technologies will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0055] Figure 1 A schematic flowchart of a method for identifying chip unpacking provided by the present invention is shown;

[0056] Figure 2 This diagram illustrates a device for identifying chip unpacking according to an embodiment of the present invention;

[0057] Figure 3 A schematic diagram of a terminal device provided in an embodiment of the present invention is shown. Detailed Implementation

[0058] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of the invention. However, those skilled in the art will understand that the invention can be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods are omitted so as not to obscure the description of the invention with unnecessary detail.

[0059] This invention provides a method and apparatus for identifying chip unpacking, in order to solve the technical problem that existing methods often cannot accurately locate the region of interest.

[0060] First, this invention provides a method for identifying chip unpacking. Please refer to [link / reference]. Figure 1 , Figure 1 A schematic flowchart of a method for identifying chip unpacking provided by the present invention is shown. Figure 1 As shown, the method for unlocking the identification chip may include the following steps:

[0061] Step 101: Acquire the current real-time image and rotate the current real-time image to a preset direction to obtain the current chip image; wherein, the preset direction refers to the direction corresponding to the standard chip area in the standard template image;

[0062] Since there may be inconsistencies in chip orientation during the chip unpacking process, it is necessary to rotate and transform the acquired real-time image to make its orientation completely consistent with the chip orientation in a pre-set "standard template image".

[0063] The standard template image is a reference image of a known high-quality chip that is in a normal, unopened state. The preset orientation is the orientation of the chip region (chip body) within this standard template image. This ensures spatial comparability between the current chip image and the standard template image. Subsequent feature extraction and similarity comparison rely on this orientational alignment.

[0064] Specifically, step 101 includes steps 1011 to 1014:

[0065] Step 1011: Acquire an image of the unopened chip and extract the unopened chip area from the image;

[0066] Before the chip unpacking process begins (i.e., when the chip is completely unpacked), an image of the specific chip is first acquired. Then, edge detection is used to identify and segment the area containing the chip itself (i.e., the "unpacked chip area") from this entire image. This area includes the package itself, excluding background, fixtures, and other irrelevant parts. Obtaining a clean image area containing the target chip (especially its package) provides the basis for subsequent steps.

[0067] Step 1012: Extract the current identification graphic from the unopened chip area; wherein, the current identification graphic refers to the product identification, mark or specific pattern printed on the chip packaging area;

[0068] Precisely locate and isolate the current identification graphic on the package. The current identification graphic refers to the product identification, mark, or specific pattern printed on the chip package area.

[0069] The current identifier graphics have clear, stable, and easily detectable geometric features (such as edges, corners, and specific markings). Segmentation based on color / texture is an existing technique and will not be described further here.

[0070] Step 1013: Extract the current orientation of the current identifier graphic;

[0071] Analyze the current logo obtained in the previous step, calculate and determine its orientation angle (i.e., "current direction") in the image coordinate system.

[0072] Specifically, step 1013 includes steps A1 to A6:

[0073] Step A1: Extract the standard logo graphic from the standard template image;

[0074] The extraction logic for standard identification graphics is the same as that for current identification graphics, and will not be repeated here. Standard identification graphics refer to product identification, logos, or specific patterns printed on the chip packaging area.

[0075] Step A2: Construct a first coordinate system with the center of the standard package area as the origin and the length and width directions as axes;

[0076] Establish a reference coordinate system closely related to the geometry of the standard package area. Subsequent point sampling will be performed in this coordinate system to ensure that the position of the sampling point is stable relative to the center of the package area.

[0077] Step A3: Based on the first coordinate system, extract multiple first sampling points on the edge of the standard logo graphic within a preset angle range at fixed horizontal coordinate intervals; wherein, the preset angle range includes 0 degrees to 90 degrees, 90 degrees to 180 degrees, 180 degrees to 270 degrees, or 270 degrees to 360 degrees.

[0078] The preset angle range is one of four 90-degree quadrants (0-90°, 90-180°, 180-270°, 270-360°). This means the system only selects one 90-degree quadrant (e.g., the lower left quadrant) for sampling. Within that selected 90-degree quadrant, the system moves along the X-axis of the first coordinate system at fixed pixel intervals (or physical intervals). For each horizontal coordinate position (x_i) reached, the point on the corresponding vertical line, moving outward from the center, intersects the edge of the standard identifier graphic and is taken as the sampling point P_std_i. This results in a set of sampling points {P_std_1, P_std_2, ..., P_std_N}, all located on the boundary of the same selected 90-degree quadrant.

[0079] Obtain a set of stable, known-location edge reference points within a specific local region (one quadrant) of the standard graphic representation. Choosing a quadrant can reduce computational complexity and potentially avoid interference from symmetry.

[0080] Step A4: Construct a second coordinate system with the center of the current logo graphic as the origin and the length and width directions as axes;

[0081] Establish a local coordinate system for the current icon, aligning its axes with its estimated principal and secondary axes, in preparation for sampling at its edges. This coordinate system is independent of its global rotation angle.

[0082] Step A5: Based on the second coordinate system, extract multiple second sampling points on the edge of the current identifier graphic at fixed horizontal coordinate intervals within multiple current angle ranges; wherein, the multiple current angle ranges include 0 degrees to 90 degrees, 90 degrees to 180 degrees, 180 degrees to 270 degrees, and 270 degrees to 360 degrees;

[0083] The multiple current angle ranges include all four 90-degree quadrants (0-90°, 90-180°, 180-270°, 270-360°). This means that the system will sample separately at the edges of each 90-degree quadrant of the current icon.

[0084] Within each quadrant, move along the X-axis of the second coordinate system at the same fixed intervals as in step A3.

[0085] For each quadrant and each moved horizontal coordinate position (x_j), find the point on the vertical line corresponding to that horizontal coordinate that intersects with the edge of the current identifier graphic, and use it as a sampling point. Ultimately, four sets of sampling points will be obtained, covering the edge of the entire encapsulation area: {P_cur_quad1}, {P_cur_quad2}, {P_cur_quad3}, {P_cur_quad4}.

[0086] Acquire a set of uniformly distributed sampling points along the entire edge of the current logo graphic. The sampling strategy (fixed x-axis interval) is consistent with the sampling strategy of the standard template.

[0087] Step A6: Calculate the current direction of the current identification graphic based on multiple first sampling points and multiple second sampling points.

[0088] By comparing the spatial relationship between the local reference point set (one quadrant) of the standard encapsulation area and the global point set (the entire edge) of the current logo graphic, the rotation angle difference (i.e., the current direction) of the current logo graphic relative to the standard encapsulation area is accurately calculated.

[0089] In the embodiments corresponding to steps A1 to A6, a local reference point ({P_std}) in one quadrant of the standard template is used to match the global point set ({P_cur}) of the complete edge of the current identifier graphic. The matching process requires simultaneously determining the optimal matching quadrant and the optimal rotation angle. By utilizing the rich geometric information of the identifier graphic (multiple sampling points) and minimizing the error through optimized matching, the sub-pixel level accurate rotation angle θ can be calculated, which is significantly better than methods that rely solely on the principal axis or a few feature points. For packages that are close to rectangular or square, there may be symmetry confusion at 90°, 180°, and 270°. By forcibly matching a specific quadrant (the standard template only samples one quadrant) and searching for the optimal rotation and quadrant correspondence, these symmetric directions can be effectively distinguished, avoiding 180° errors. If the current chip is rotated by 90°, the actual edge quadrant shape in {P_cur} corresponding to the sampling quadrant position of the standard template will be completely different, and the matching distance will be large. However, after rotating by 90°, the shape matching degree of adjacent quadrants will be higher, thus calculating the correct 90° offset. By densely sampling and identifying edge points of the graphic (especially for the current encapsulation which uses global sampling) and optimizing point set matching, sub-pixel-level angular resolution is achieved. The standard template only needs to store the point set of one quadrant, reducing the computational burden, while the global sampling of the current encapsulation ensures the accuracy and robustness of the matching.

[0090] Specifically, step A6 includes steps A61 to A65:

[0091] Step A61: Calculate the first distance between multiple first sampling points and the origin, and construct a first distance vector from the multiple first distances;

[0092] For each first sampling point P_std_i extracted from the standard template image (these points are all located within the same selected preset angle range / quadrant, such as the 0-90° quadrant), calculate the Euclidean distance d_std_i = ||P_std_i - O_std|| from the point to its first coordinate system origin O_std (i.e., the center of the standard package area).

[0093] Following a fixed order of these sampling points within a preset angular range (quadrant) (e.g., arranged according to fixed x-coordinate intervals), all calculated distance values ​​d_std_1, d_std_2, ..., d_std_N are combined into an ordered list or array. This ordered set is the first distance vector V_std.

[0094] The geometric shape information (distance distribution from sampling points to the center) of the standard template in a specific quadrant is abstracted into a one-dimensional numerical sequence (vector). This vector describes the variation characteristics of the "radius" of the quadrant's edge contour relative to the center.

[0095] Step A62: Calculate the second distance between multiple second sampling points and the origin, and construct a second distance vector from the multiple second distances;

[0096] For each second sampling point P_cur_j extracted from the current logo graphic image (these points are distributed in all four current angle ranges / quadrants), calculate the Euclidean distance d_cur_j = ||P_cur_j - O_cur|| from the point to its second coordinate system origin O_cur (i.e., the center of the current logo graphic).

[0097] Group the global sampling points of the current identifier graphic (distributed across four quadrants) by quadrant. For each quadrant q (q=1,2,3,4, corresponding to 0-90°, 90-180°, 180-270°, 270-360° respectively), extract all sampling points {P_cur_q} belonging to that quadrant q. Calculate their distances {d_cur_q} to O_cur according to the fixed order of these points within quadrant q (the same rules as standard template sampling, such as arranged according to fixed horizontal coordinate intervals). Combine these distance values ​​sequentially into an ordered list or array to form the second distance vector V_cur_q for that quadrant q.

[0098] Ultimately, four second distance vectors are obtained: V_cur_quad1, V_cur_quad2, V_cur_quad3, and V_cur_quad4, each representing the contour distance feature of a complete quadrant.

[0099] The geometric shape information of each complete quadrant of the current identified graphic is also abstracted into its own one-dimensional distance vector. This prepares for subsequent quadrant matching.

[0100] Step A63: Calculate the vector similarity between the second distance vector and the first distance vector for each of the multiple current angle ranges;

[0101] For each current angle range (i.e., each quadrant q), its corresponding second distance vector V_cur_q is compared with the first distance vector V_std of the standard template.

[0102] Calculate the vector similarity Sim_q between them. Vector similarity is calculated using cosine similarity or Pearson correlation coefficient.

[0103] Quantitatively evaluate the degree of matching between the edge contour features (denoted by V_cur_q) of each complete quadrant of the current identifier graphic and the edge contour features (denoted by V_std) of a specific reference quadrant of the standard template. The higher the similarity Sim_q, the more similar the shape features of the current q-th quadrant are to the standard reference quadrant.

[0104] Step A64: Calculate the directional angle between the current angle range and the preset angle range corresponding to the maximum vector similarity;

[0105] Find the maximum value, Sim_max, among the four quadrant similarity values ​​(Sim_quad1, Sim_quad2, Sim_quad3, Sim_quad4) calculated in step A63. Determine the current angle range (quadrant) q_max corresponding to this maximum value (for example, if Sim_quad3 is the largest, then q_max = Quad3, corresponding to an angle range of 180-270°).

[0106] The sampling points of the standard template come from only one preset angle range (quadrant) q_std (e.g., the preset is Quad1, 0-90°). The angular positions of q_max (the current quadrant with the highest matching degree) and q_std (the reference quadrant of the standard template) are compared. The directional angle θ is the angular difference between these two quadrants. The specific calculation method depends on the quadrant numbering / order definition:

[0107] If the quadrants are numbered counterclockwise (Quad1: 0-90°, Quad2: 90-180°, Quad3: 180-270°, Quad4: 270-360°), then θ = (q_max_index - q_std_index) * 90°.

[0108] For example: q_std = Quad1 (index=1), q_max = Quad3 (index=3), then θ = (3 - 1) * 90° = 180°.

[0109] If the calculation result is negative or greater than 270°, it may be necessary to adjust to the range of [-180°, 180°] or [0°, 360°] (for example, -90° is equivalent to 270°) and take the minimum rotation angle.

[0110] By finding the current quadrant that is most similar to the standard reference quadrant, the discrete rotation angle offset (a multiple of 90°) of the current logo graphic relative to the standard template is directly determined.

[0111] Step A65: Take the included angle of the directions as the current direction.

[0112] In the embodiments corresponding to steps A61 to A65, high real-time performance is achieved based on fast distance calculation and one-dimensional vector similarity comparison. It remains completely unaffected by translations within the image plane, perfectly recognizes rotations that are multiples of 90°, and has a certain tolerance for local edge noise and global illumination / slight scale changes. This method is particularly suitable as a fast orientation correction step in chip unpacking visual guidance or inspection systems, handling the common scenario of rectangular / square chips placed at standard discrete angles (0°, 90°, 180°, 270°), providing a foundation for subsequent accurate ROI extraction and state analysis. A computationally efficient and simple algorithm is provided to determine the rotation angle (current direction) of the chip packaging area relative to a standard template that is a multiple of 90°. Its core is to convert the shape information of the packaging edge into a one-dimensional distance vector and match the optimal rotation posture through quadrant similarity comparison.

[0113] Step 1014: During the chip unpacking process, acquire the current real-time image, and rotate the current real-time image to a preset direction based on the current direction to obtain the current chip image.

[0114] A rotation transformation is applied to the acquired real-time image. The rotation angle is the angle value of rotating the image in the reverse direction by the "current direction" (or equivalently, rotating it in the forward direction by an angle that brings the direction to zero). This compensates for the random orientation of the chip during initial placement, aligning it with a preset orientation. Using the orientation reference calculated for the same chip before unpacking, it corrects for slight movement during unpacking or inherent orientation deviations during initial placement, ensuring that subsequent ROI extraction and similarity comparison are performed in the same direction as the standard template image.

[0115] Only by precisely rotating the current real-time image to the same preset orientation as the standard template image can we ensure that the ROI coordinates defined in the standard template can be accurately mapped to the corresponding physical location on the current image. Orientation alignment is the foundation of spatial coordinate matching.

[0116] Comparing the visual similarity (whether at the pixel, feature, or structural level) of two regions is only reliable when the images are strictly aligned in orientation and position. Inconsistent orientation introduces significant differences that are independent of the open state, leading to unreliable similarity results and misjudgments (false positives / false negatives).

[0117] In the embodiments corresponding to steps 1011 to 1014, an orientation reference based on the characteristics of its own package is extracted for each individual chip, and this individualized reference is used to perform high-precision orientation correction on the real-time image during the unpacking process. This effectively eliminates the orientation deviation caused by the slight rotation during the initial placement and unpacking of the chip, ensuring that subsequent key area extraction and state comparison are performed in a strictly aligned spatial coordinate system, thereby greatly improving the accuracy, robustness, and automation level of the chip unpacking state recognition method.

[0118] Step 102: Obtain the region of interest in the standard template image; wherein the region of interest includes the chip die area, the wire bonding area and / or the pin area;

[0119] In the standard template image, one or more specific sub-regions (Regions of Interest, ROIs) are pre-marked. ROIs are critical structural parts in the chip unpacking process, including but not limited to the die area, wire bonding area, and / or pin area. The die area is the core silicon wafer portion of the chip, which should be exposed after unpacking. The wire bonding area is the area of ​​fine metal lines connecting the solder joints and lead frames on the die; it should be clearly visible and undamaged after unpacking. The pin area is the metal pin portion that connects the chip to external circuitry.

[0120] Step 103: Extract the region to be identified corresponding to the region of interest in the current chip image;

[0121] The region corresponding to the template ROI is located and extracted on the current chip image after orientation alignment. Based on the mapping relationship, a sub-image region that strictly corresponds to the standard template ROI in position (i.e., has the same coordinate position) is cut out from the current chip image as the "region to be identified".

[0122] Step 104: Control the chip unpacking process based on the regional similarity between the region of interest and the region to be identified corresponding to the region of interest.

[0123] For each "region of interest" (in the template image) defined in step 102 and extracted in step 103, and its "corresponding region to be identified" (in the current image), the visual similarity (similarity score) between them is calculated. The next action of the opening device is determined based on the calculated similarity (which may be the similarity of one or more regions).

[0124] Specifically, step 104 includes steps 1041 to 1043:

[0125] Step 1041: Calculate the region similarity between the region of interest and the region to be identified corresponding to the region of interest;

[0126] Quantify the degree of difference between the current visual state of each key region (die, bond wire, pin) after unpacking and the standard template (normal state). The lower the region similarity, the greater the difference between the state of that region and the normal state.

[0127] Specifically, step 1041 includes steps B1 to B8:

[0128] Step B1: Extract the first pixel value and the second pixel value corresponding to the same pixel position in the region of interest and the region to be identified corresponding to the region of interest;

[0129] The first pixel value is the pixel value of that point in the standard template image. The second pixel value is the pixel value of the corresponding point in the current region to be identified.

[0130] Step B2: Calculate the absolute difference between the first pixel value and the second pixel value;

[0131] Subtracting the first and second pixel values ​​corresponding to the same pixel location and taking the absolute value yields the absolute difference. Calculating this absolute difference allows for a precise measurement of the differences between each pixel, providing a more accurate similarity analysis.

[0132] Step B3: If the absolute value difference is less than the first value, then the position of that pixel is taken as the position of the pixel of interest;

[0133] If the difference is less than a certain threshold (a first value), the pixel is considered similar in both images and is selected as the pixel of interest. By setting a threshold, similar pixels can be effectively filtered out, thereby improving the accuracy of similarity calculation. The first value is 10.

[0134] Step B4: If the absolute value difference is not less than the first value, then the position of that pixel is taken as the position of a non-interesting pixel.

[0135] If the difference is greater than or equal to the first value, the pixel is considered to be dissimilar in the two images and is marked as a non-interesting pixel location.

[0136] Step B5: Extract the adjacent pixel positions corresponding to each pixel position of interest to obtain the current image region composed of multiple adjacent pixel positions of interest or a single pixel position of interest;

[0137] After determining the location of the pixel of interest, extract the locations of its neighboring pixels of interest to form a larger region. By aggregating neighboring pixels of interest, the similarity of image regions can be reflected more comprehensively.

[0138] Step B6: Count the number of pixel positions in the current image region;

[0139] Step B7: Select the current image region with a number of pixel positions greater than the second number as the target image region;

[0140] If the number of pixels of interest in the current image region exceeds a certain threshold (the second threshold), then the region is identified as the target image region. By setting a threshold, regions containing a large number of similar pixels can be filtered out, improving the effectiveness of similarity calculation.

[0141] If the second quantity is 30, then if the current image region has 50 pixels of interest, it is marked as the target image region.

[0142] Step B8: Calculate the region similarity based on the number of pixel positions corresponding to the target image region and the absolute value difference of each pixel position.

[0143] By comprehensively utilizing pixel count and difference values, a more comprehensive and accurate measure of regional similarity is provided, thereby improving the accuracy of image matching and recognition.

[0144] In the embodiments corresponding to steps B1 to B8, by setting specific values ​​(such as a first value of 10 and a second quantity of 30), the steps and standards for similarity calculation can be precisely controlled, ensuring the efficiency and accuracy of the recognition process. These logical steps and values ​​not only improve the precision of similarity calculation but also effectively filter and aggregate similar image regions, thereby enhancing the reliability and security of the entire chip unpacking process.

[0145] Specifically, step B8 includes steps B81 to B84:

[0146] Step B81: Obtain the maximum absolute difference;

[0147] Step B82: Calculate the quality weight for each pixel location based on the maximum absolute difference and the absolute difference at each pixel location; where, quality weight = d i d represents the absolute difference at the position of the i-th pixel. max This represents the maximum absolute value difference. Indicates the attenuation coefficient;

[0148] This aligns better with human visual sensitivity to differences (high tolerance for small differences, strong punishment for large differences). Control sensitivity (e.g., setting sensitivity when image noise is high) (Reduce the severity).

[0149] Step B83: Calculate the region contribution based on the number of pixel locations corresponding to the target image region and the quality weight corresponding to each pixel location; where, region contribution = n j w represents the number of pixel positions corresponding to the j-th target image region. i This represents the quality weight corresponding to the position of the i-th pixel.

[0150] For each target image region, a weighted effective pixel count is calculated, with the weight in parentheses representing the region's average quality weight. The region contribution considers both the region's average similarity and its size. This balances the contributions of small but highly similar regions with large but low-similarity regions.

[0151] Step B84: The average value of the regional contribution corresponding to multiple target image regions is taken as the regional similarity.

[0152] A comprehensive region similarity score can be obtained by calculating the average regional contribution of all target image regions. This score reflects the overall similarity between the region of interest and the region to be identified.

[0153] Since the regional contribution score takes into account both the similarity of pixels within the region and the size of the region, the final regional similarity score can more comprehensively reflect the similarity relationship between two regions and reduce the bias caused by a single factor.

[0154] In the embodiments corresponding to steps B81 to B84, the similarity between the region of interest and the region to be identified can be effectively evaluated by standardizing pixel differences, using exponential decay weights, and comprehensively considering region size and similarity. It not only considers pixel-level detail differences but also ensures the rationality and robustness of large-scale statistics through the calculation of region contribution, thus providing an accurate and comprehensive method for calculating region similarity.

[0155] Step 1042: When the similarity of the region is lower than the preset similarity, continue to execute the chip unpacking process and acquire subsequent real-time images;

[0156] Send instructions to the opening equipment (such as a laser opening machine or a chemical opening tank controller) to maintain or continue the opening operation (e.g., maintain laser power, continue injecting etching solution, move to the next opening point, etc.). After the opening process continues for a period of time (or at the next preset detection point), acquire a new real-time image and execute steps 101 to 104.

[0157] When the area similarity is lower than the preset similarity, it means that the sealant has not been completely removed, the bare die has not been fully exposed, or there are still obstructions in the bonding wire area. Therefore, the system decides to continue the unsealing operation to improve the condition of these areas (make them more similar to the standard template) in subsequent steps.

[0158] Acquiring subsequent images is for the purpose of the next detection-decision cycle, forming a closed-loop control. The system will continue to monitor until all areas meet the requirements.

[0159] Step 1043: When the similarity of the regions is not lower than the preset similarity, stop the chip unpacking process.

[0160] When the similarity of all regions is not lower than the preset similarity, it means that the status of all monitored key regions has reached or exceeded the expected normal state (the similarity of all regions is not lower than the threshold). Stop production as soon as the quality requirements are met (all regions meet the standards) to ensure product quality (avoid overprocessing damage) and optimize the production cycle (do not waste time on completed steps).

[0161] In the embodiments corresponding to steps 1041 to 1043, instead of relying on preset fixed time, fixed energy, or fixed steps, the decision to continue unpacking is dynamically made based on the current actual visual state of each critical area (quantified by similarity measurement). This automatically adapts to minor differences between different chips, changes in the state of the unpacking tool (such as laser power attenuation, changes in etchant concentration), and environmental fluctuations. Unpacking only stops when all critical areas meet the requirements, ensuring complete unpacking and quality compliance. If even one area fails to meet the standard, unpacking continues to prevent under-unpacking (outflow of defective products); unpacking stops immediately when all areas meet the standard to prevent over-unpacking (damage to the chip, waste of resources). The process of "continuing to execute...and acquiring subsequent real-time images" constitutes a closed-loop control loop, continuously monitoring and adjusting until all conditions are met. By precisely controlling the unpacking endpoint, the integrity and cleanliness of critical structures (bare die, bonding wires, pins) after unpacking are ensured. Unpacking stops immediately upon meeting quality requirements, avoiding unnecessary additional unpacking time / energy / material consumption.

[0162] In the embodiments corresponding to steps 101 to 104, rotating the current real-time image to a preset direction ensures consistent image orientation for each processing step. Since chip images may exhibit different features in different directions, a unified image orientation facilitates feature extraction and matching, improving recognition accuracy and consistency. Using a standard template image as a reference ensures a reliable benchmark throughout the recognition process, reducing errors caused by variations in image orientation and angle. By acquiring regions of interest (such as the die area, wire bonding area, and pin area) from the standard template image and extracting the corresponding region to be identified in the current chip image, key chip components can be precisely located. This process avoids recognition errors caused by inaccurate region extraction in traditional methods. Judgment based on the similarity between the region of interest and the corresponding region to be identified further improves recognition accuracy. Similarity calculation effectively distinguishes subtle differences, ensuring the reliability of the recognition results. In summary, this invention achieves high efficiency, precision, and automation in the chip unpacking process, significantly improving unpacking efficiency and recognition accuracy.

[0163] like Figure 2 This invention provides a device for identifying chip unpacking; please refer to [link / reference]. Figure 2 , Figure 2 A schematic diagram of a device for identifying chip unpacking provided by the present invention is shown, as follows: Figure 2 The device shown includes:

[0164] The acquisition unit 21 is used to acquire the current real-time image and rotate the current real-time image to a preset direction to obtain the current chip image; wherein, the preset direction refers to the direction corresponding to the standard chip area in the standard template image;

[0165] The acquisition unit 22 is used to acquire the region of interest in a standard template image; wherein the region of interest includes a chip die area, a wire bonding area and / or a package pin area;

[0166] Extraction unit 23 is used to extract the region to be identified corresponding to the region of interest in the current chip image;

[0167] Control unit 24 is used to control the chip unpacking process based on the regional similarity between the region of interest and the region to be identified corresponding to the region of interest.

[0168] This invention provides a device for identifying chip unpacking. By rotating the current real-time image to a preset orientation, it ensures consistent image orientation for each processing operation. Since chip images may exhibit different features in different orientations, a unified image orientation facilitates feature extraction and matching, improving the accuracy and consistency of identification. Using a standard template image as a reference ensures a reliable benchmark throughout the identification process, reducing errors caused by variations in image orientation and angle. By acquiring regions of interest (such as the die area, wire bonding area, and pin area) from the standard template image and extracting the corresponding region to be identified in the current chip image, the key components of the chip can be accurately located. This process avoids identification errors caused by inaccurate region extraction in traditional methods. Judgment is based on the similarity between the region of interest and the corresponding region to be identified, further improving identification accuracy. Similarity calculation effectively distinguishes subtle differences, ensuring the reliability of the identification results. In summary, this invention achieves high efficiency, accuracy, and automation in the chip unpacking process, significantly improving unpacking efficiency and identification accuracy.

[0169] Figure 3 This is a schematic diagram of a terminal device provided in an embodiment of the present invention. Figure 3 As shown, a terminal device 3 in this embodiment includes: a processor 30, a memory 31, and a computer program 32 stored in the memory 31 and executable on the processor 30, such as a program for identifying chip unpacking. When the processor 30 executes the computer program 32, it implements the steps in the various embodiments of the method for identifying chip unpacking described above, for example... Figure 1 Steps 101 to 104 are shown. Alternatively, when the processor 30 executes the computer program 32, it implements the functions of each unit in the above-described device embodiments, for example... Figure 2 The function of the unit shown.

[0170] For example, the computer program 32 can be divided into one or more units, which are stored in the memory 31 and executed by the processor 30 to complete the present invention. The one or more units can be a series of computer program instruction segments capable of performing a specific function, which describe the execution process of the computer program 32 in the terminal device 3. For example, the specific functions of each unit of the computer program 32 can be divided as follows:

[0171] The acquisition unit is used to acquire the current real-time image and rotate the current real-time image to a preset direction to obtain the current chip image; wherein, the preset direction refers to the direction corresponding to the standard chip area in the standard template image;

[0172] An acquisition unit is used to acquire a region of interest in a standard template image; wherein the region of interest includes a die area, a wire bonding area, and / or a package pin area;

[0173] Extraction unit, used to extract the region to be identified corresponding to the region of interest in the current chip image;

[0174] The control unit is used to control the chip unpacking process based on the regional similarity between the region of interest and the region to be identified corresponding to the region of interest.

[0175] The terminal device includes, but is not limited to, a processor 30 and a memory 31. Those skilled in the art will understand that... Figure 3 This is merely an example of a terminal device 3 and does not constitute a limitation on a terminal device 3. It may include more or fewer components than shown, or combine certain components, or different components. For example, the terminal device may also include input / output devices, network access devices, buses, etc.

[0176] The processor 30 can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor.

[0177] The memory 31 can be an internal storage unit of the terminal device 3, such as a hard disk or memory of the terminal device 3. The memory 31 can also be an external storage device of the terminal device 3, such as a plug-in hard disk, smart media card (SMC), secure digital card (SD), flash card, etc., equipped on the terminal device 3. Furthermore, the memory 31 can include both internal and external storage units of the terminal device 3. The memory 31 is used to store the computer program and other programs and data required by the roaming control device. The memory 31 can also be used to temporarily store data that has been output or will be output.

[0178] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0179] It should be noted that the information interaction and execution process between the above-mentioned devices / units are based on the same concept as the method embodiments of the present invention. For details on their specific functions and technical effects, please refer to the method embodiments section, which will not be repeated here.

[0180] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is merely an example. In practical applications, the above functions can be assigned to 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 embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit. Furthermore, the specific names of the functional units and modules are only for easy differentiation and are not intended to limit the scope of protection of this invention. The specific working process of the units and modules in the above system can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0181] This invention also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps described in the various method embodiments above.

[0182] This invention provides a computer program product that, when run on a mobile terminal, enables the mobile terminal to implement the steps described in the above-described method embodiments.

[0183] If the integrated unit is implemented as 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, all or part of the processes in the methods of the above embodiments of the present invention can be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include at least: any entity or device capable of carrying the computer program code to a photographing device / terminal device, a recording medium, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium. Examples include USB flash drives, portable hard drives, magnetic disks, or optical disks.

[0184] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0185] Those skilled in the art will recognize that the units and algorithm steps of the various examples 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 implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0186] In the embodiments provided by this invention, it should be understood that the disclosed apparatus / network devices and methods can be implemented in other ways. For example, the apparatus / network device embodiments described above are merely illustrative. For instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0187] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; they may be located in one place or distributed across multiple network units.

[0188] It should be understood that, when used in this specification and the appended claims, the term "comprising" indicates the presence of the described features, integrals, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or collections thereof.

[0189] It should also be understood that the term “and / or” as used in this specification and the appended claims refers to any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0190] As used in this specification and the appended claims, the term "if" may be interpreted, depending on the context, as "when," "once," "in response to determination," or "in response to detection." Similarly, the phrase "if determined" or "if [the described condition or event] is detected" may be interpreted, depending on the context, as meaning "once determined," "in response to determination," "once [the described condition or event] is detected," or "in response to detection of [the described condition or event]."

[0191] Furthermore, in the description of this invention and the appended claims, the terms "first," "second," "third," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0192] References to "one embodiment" or "some embodiments" as described in this specification mean that one or more embodiments of the invention include a specific feature, structure, or characteristic described in connection with that embodiment. Therefore, the phrases "in one embodiment," "in some embodiments," "in other embodiments," "in still other embodiments," etc., appearing in different parts of this specification do not necessarily refer to the same embodiment, but rather mean "one or more, but not all, embodiments," unless otherwise specifically emphasized. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless otherwise specifically emphasized.

[0193] The above-described embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included within the protection scope of the present invention.

Claims

1. A method of identifying the opening of a chip, characterized in that, The method for identifying the opening of the chip comprises: Collecting a current real-time image and rotating the current real-time image to a preset direction to obtain a current chip image; wherein the preset direction refers to a direction corresponding to a standard chip region in a standard template image; Obtaining a region of interest in the standard template image; wherein the region of interest comprises a chip die region, a wire bonding region and / or a pin region; the standard template image is a reference image of a chip with a known quality, a qualified opening state; Extracting a to-be-identified region corresponding to the region of interest in the current chip image; Controlling a chip opening process according to a region similarity between the region of interest and the to-be-identified region corresponding to the region of interest.

2. The method of claim 1, wherein the opening of the chip is identified by the fact that the chip is not in the package. The step of collecting a current real-time image and rotating the current real-time image to a preset direction to obtain a current chip image comprises: ​ Collecting an unopened chip image and extracting an unopened chip region in the unopened chip image; Extracting a current identification pattern in the unopened chip region; wherein the current identification pattern refers to a product identification, a logo or a specific pattern printed on a chip packaging region; Extracting a current direction of the current identification pattern; During the chip opening process, collecting a current real-time image and rotating the current real-time image to a preset direction based on the current direction to obtain a current chip image.

3. The method for identifying chip unpacking as described in claim 2, characterized in that, The step of extracting a current direction of the current identification pattern comprises: Extracting a standard identification pattern in the standard template image; Constructing a first coordinate system with the center of the standard packaging region as the origin and the length and width directions as the axes; Based on the first coordinate system, extracting a plurality of first sampling points on the edge of the standard identification pattern at a fixed horizontal coordinate interval within a preset angle range; wherein the preset angle range comprises 0 degrees to 90 degrees, 90 degrees to 180 degrees, 180 degrees to 270 degrees or 270 degrees to 360 degrees; Constructing a second coordinate system with the center of the current identification pattern as the origin and the length and width directions as the axes; Based on the second coordinate system, extracting a plurality of second sampling points on the edge of the current identification pattern at a fixed horizontal coordinate interval within a plurality of current angle ranges; wherein the plurality of current angle ranges comprise 0 degrees to 90 degrees, 90 degrees to 180 degrees, 180 degrees to 270 degrees and 270 degrees to 360 degrees; Calculating the current direction of the current identification pattern according to the plurality of first sampling points and the plurality of second sampling points.

4. The method of claim 3, wherein the opening of the chip is identified by the fact that the chip is not in the package. 5 The step of calculating the current direction of the current identification pattern according to the plurality of first sampling points and the plurality of second sampling points comprises: Calculating a plurality of first distances between the plurality of first sampling points and the origin and constructing the plurality of first distances into a first distance vector; Calculating a plurality of second distances between the plurality of second sampling points and the origin and constructing the plurality of second distances into a second distance vector; Respectively calculating a vector similarity between the second distance vector and the first distance vector corresponding to each of the plurality of current angle ranges; Calculating a direction included angle between a current angle range corresponding to a maximum vector similarity and a preset angle range; Taking the direction included angle as the current direction.

5. The method of claim 1, wherein the opening of the chip is identified by the fact that the chip is not in the package. 5 The step of controlling the chip opening process according to the region similarity between the region of interest and the region to be identified corresponding to the region of interest comprises: calculating the region similarity between the region of interest and the region to be identified corresponding to the region of interest; when the region similarity is lower than a preset similarity, continuing to execute the chip opening process and collecting subsequent real-time images; when the region similarity is all not lower than the preset similarity, stopping the chip opening process.

6. The method of claim 5, wherein the opening of the chip is identified by the fact that the chip is not in the package. 5 The step of calculating the region similarity between the region of interest and the region to be identified corresponding to the region of interest comprises: extracting a first pixel value and a second pixel value corresponding to a same pixel point position in the region of interest and the region to be identified corresponding to the region of interest; calculating an absolute value difference between the first pixel value and the second pixel value; if the absolute value difference is less than a first value, taking the pixel point position as an interested pixel position; if the absolute value difference is not less than the first value, taking the pixel point position as a non-interested pixel position; extracting adjacent interested pixel positions corresponding to each interested pixel position to obtain a current image region composed of a plurality of adjacent interested pixel positions or a single interested pixel position; counting the number of pixel positions in the current image region; taking a current image region with a number of pixel positions greater than a second number as a target image region; calculating the region similarity according to the number of pixel positions corresponding to the target image region and the absolute value difference corresponding to each pixel point position.

7. The method for identifying chip unpacking as described in claim 6, characterized in that, The step of calculating the region similarity according to the number of pixel positions corresponding to the target image region and the absolute value difference corresponding to each pixel point position comprises: obtaining a maximum absolute value difference; According to the maximum absolute value difference and the absolute value difference corresponding to each pixel point position, a quality weight corresponding to each pixel point position is calculated; wherein the quality weight , represents the absolute value difference corresponding to the i-th pixel point position, represents the maximum absolute value difference, represents the attenuation coefficient; According to the number of pixel positions corresponding to the target image region and the quality weight corresponding to each pixel position, a region contribution degree is calculated; wherein the region contribution degree , represents the number of pixel positions corresponding to the jth target image region, represents the quality weight corresponding to the ith pixel position; taking the average of the region contribution degrees corresponding to a plurality of target image regions as the region similarity.

8. A device for identifying the opening of a chip, characterized in that The device for identifying chip opening comprises: a collection unit configured to collect a current real-time image and rotate the current real-time image to a preset direction to obtain a current chip image, wherein the preset direction refers to a direction corresponding to a standard chip region in a standard template image; an obtaining unit configured to obtain a region of interest in a standard template image, wherein the region of interest comprises a chip die region, a wire bonding region and / or a packaging pin region; and the standard template image is a reference image of a chip with a known quality, a qualified opening state and a normal opening state; an extracting unit configured to extract a region to be identified corresponding to the region of interest in the current chip image; a control unit configured to control a chip opening process according to a region similarity between the region of interest and the region to be identified corresponding to the region of interest.

9. A terminal device, comprising: The terminal device comprises a memory, a processor and a program for identifying chip opening stored in the memory and executable on the processor, and the program for identifying chip opening is configured to implement the steps in the method for identifying chip opening according to any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, the computer-readable storage medium comprising: The computer program is executed by the processor to implement the steps in the method for identifying chip opening according to any one of claims 1 to 7.

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