Defect detection method for flexible die cutting circuit board FDC

Abstract

The invention belongs to the field of precision electronic manufacturing detection, and provides a defect detection method for a flexible die cutting circuit board (FDC), which comprises the following steps of: acquiring an image of the FDC to be detected; segmenting the image, identifying a copper foil area image, and extracting the copper foil area image; graying the copper foil area image to obtain a copper foil area grayscale image; calculating an oxygen display gray value of the gray image of the copper foil area, and obtaining an oxidation area through the oxygen display gray value; and carrying out gray momentum increase analysis on the oxidation region, and obtaining a copper foil oxidation core region according to a gray momentum increase analysis result. According to the defect detection method provided by the embodiment of the invention, the identification process of the oxidation region can be further optimized through gray momentum lifting analysis, so that the transition region between the oxidation region and the non-oxidation region can be identified more accurately, the limitation of static threshold judgment is avoided, and the detection accuracy of the oxidation region is improved.

Description

Technical Field

[0001] The invention belongs to the field of precision electronic manufacturing detection, and in particular relates to a defect detection method for a flexible die-cut circuit board (FDC). Background Art

[0002] Since the patent number CN107367465A, entitled "A method for detecting oxidation of copper foil of FPC flexible board", relies on color components (especially red R components) to extract oxidation areas, and judges the degree of oxidation by simple grayscale difference, this method has the problem of different color saturation or when copper oxide is similar to other factors (such as solder resist, copper foil itself, etc.), it is difficult to accurately distinguish the oxidation area. Moreover, the threshold (128) set in this method is fixed, which is not applicable to all cases. Different oxidation degrees, ambient light conditions or color characteristics of the substrate may lead to inaccurate detection results. Moreover, since this method judges the oxidation area by grayscale difference, the difference between the oxidized copper foil and the unoxidized part is not always significant, especially in the case of light oxidation or small color change, the fixed threshold judgment will miss small or complex oxidation features and texture interference leading to misjudgment. Summary of the invention

[0003] The present invention aims to solve at least one of the technical problems in the related art to a certain extent. To this end, the first object of the present invention is to propose a defect detection method for a flexible die-cut circuit board FDC, which can further optimize the identification process of the oxidation area through grayscale momentum boosting analysis, so that the transition area between the oxidation area and the non-oxidation area can be more accurately identified, avoiding the limitations of static threshold judgment and improving the accuracy of oxidation area detection;

[0004] To achieve the above object, a first embodiment of the present invention provides a defect detection method for a flexible die-cut circuit board (FDC), the method comprising the following steps:

[0005] S100, obtaining an image of the FDC circuit board to be inspected;

[0006] S200, segmenting the FDC circuit board image to be detected, identifying the copper foil area image, and extracting the copper foil area image;

[0007] S300, graying the copper foil area image to obtain a copper foil area grayscale image;

[0008] S400, calculating the oxygen grayscale value of the grayscale image of the copper foil area, and obtaining the oxidized area through the oxygen grayscale value;

[0009] S500, performing grayscale momentum boost analysis on the oxidized area, and obtaining the oxidized core area of ​​the copper foil according to the grayscale momentum boost analysis result.

[0010] According to the defect detection method of an embodiment of the present invention, the identification process of the oxidation area can be further optimized through grayscale momentum boost analysis, so that the transition area between the oxidation area and the non-oxidation area can be more accurately identified, avoiding the limitations of static threshold judgment and improving the accuracy of oxidation area detection.

[0011] Furthermore, in step S100, obtaining the image of the FDC circuit board to be inspected includes: placing the FDC circuit board to be inspected in a fixed position, adjusting the intensity of the white ring cold light source, and using a high-resolution camera to capture a colored image of the FDC circuit board to be inspected. Since the copper foil absorbs light with a wavelength less than 580nm very well, and the reflectivity of light greater than 580nm is as high as 90%, it appears red-orange. Copper oxide absorbs light with a wavelength of 400-780nm very well, so it appears black. The solder resist covering the circuit on the copper foil has an absorption rate of 70% for light with a wavelength of 620-760nm, so it appears brown and is illuminated by a white ring light, and the contrast between the three is high.

[0012] Further, in step S200, the FDC circuit board image to be detected is segmented to identify the copper foil area image. Extracting the copper foil area image includes:

[0013] The boundary is determined by the algorithm of interest, the FDC circuit board image to be inspected is segmented, and the copper foil area image is extracted.

[0014] Furthermore, in step S300, the copper foil area image is grayed out, and obtaining the copper foil area gray image includes:

[0015] The copper foil area image is grayed out, and the copper foil area image after the graying process is referred to as the copper foil area grayscale image.

[0016] Since the patent number CN107367465A, entitled "A method for detecting oxidation of copper foil of FPC flexible board", relies on color components (especially red R components) to extract oxidation areas, and judges the degree of oxidation by simple grayscale difference, this method has the problem of different color saturation or copper oxide is similar to other factors (such as solder resist, copper foil itself, etc.), it is difficult to accurately distinguish the oxidation area. In order to solve the above problem, the present invention proposes step S400;

[0017] Further, in step S400, calculating the oxygen grayscale value of the grayscale image of the copper foil area, and obtaining the oxidized area through the oxygen grayscale value includes:

[0018] The copper foil area grayscale image is meshed by a meshing algorithm, and the mesh size is 1 / 1000 of the copper foil area grayscale image. The copper foil area grayscale image is divided into K grids, where K = 1000, and s(i) represents the grayscale value of the i-th grid of the copper foil area grayscale image, i is [1, K], and K is the number of grids after the copper foil area grayscale image is divided. The median of the grayscale values ​​in each grid in s(i) is obtained and recorded as ZD, and the average of the grayscale values ​​in each grid in s(i) is obtained and recorded as ZM;

[0019] The oxygen gray value ZP is calculated by the first equation; wherein the oxygen gray value is a gray value for judging whether it is oxidation coloration in the gray difference caused by the brightness difference between the oxidation copper foil area and the normal area under the lighting unit based on the white ring cold light source.

[0020] Among them, the method for calculating the oxygen gray value ZP in the first equation is:

[0021] Calculate the oxygen gray value ZP: subtract the absolute value of the gray range momentum from (ZM / 2), where the gray range momentum is the product of ZD and the gray momentum ratio, where the gray momentum ratio is and the ratio of (K×(ZD+ZM) / 2).

[0022] Since the grayscale value difference between the oxidized area and the normal area is generally less than half of ZM, the grayscale range momentum uses ZM / 2 as the basic grayscale, where ZD is the median of the grayscale value of the copper foil area pixel. The grayscale range momentum obtained by subtracting the grayscale of each grid and the difference between ZD and ZM from the basic grayscale ZM / 2 can effectively reduce the grayscale value impact caused by local light spots or dark spots. In the grayscale momentum ratio, (K×(ZD+ZM) / 2) is used as the denominator to reflect the momentum change of the center value of the grayscale distribution in the area. The larger the value, the more concentrated the grayscale of the area, and the more obvious the contrast between the oxidized area and the normal area. The smaller the result, the more uniform the grayscale distribution is, and a stricter oxygen grayscale value is required to distinguish the oxidized area.

[0023] The grids in s(i) whose grayscale values ​​are less than the oxygen-displaying grayscale value ZP are recorded as oxidized grids, and the area consisting of all oxidized grids in the copper foil area image is recorded as an oxidized area.

[0024] The beneficial effects of this step are: introducing dynamic adjustment of the oxygen gray value, by dynamically calculating the oxygen gray value ZP, greatly improves the sensitivity and accuracy of the oxidized area, so that the detection process of the oxidized area can adapt to different lighting conditions and scenes with color saturation changes, reduce the impact of external conditions on the detection results, refine the judgment criteria for the difference between the oxidized area and the non-oxidized area, and overcome the problem of misjudgment caused by color similarity. It avoids the decrease in detection accuracy caused by changes in color component characteristics (such as inconsistent saturation), improves the ability to extract subtle features of the oxidized area, and overcomes the confusion problem when the color of copper oxide is similar to that of the solder resist and copper foil itself.

[0025] Further, in step S500, grayscale momentum boost analysis is performed on the oxidized area, and obtaining the oxidized core area of ​​the copper foil according to the grayscale momentum boost analysis result includes:

[0026] S501, use ZOF(j) to represent the grayscale value of the grid of the jth oxidation region, the value range of the serial number j is [1, G], where G is the number of grids in the oxidation region; ZOG(j) represents the average grayscale value of the adjacent grids of the jth oxidation region grid.

[0027] Furthermore, the adjacent grid refers to the grid that shares the border with the current grid, wherein the gray value of the grid is the average gray value of all pixels in the grid, wherein the average gray value of the adjacent grids of the jth oxidation region grid is the sum of the gray values ​​of all adjacent grids of the grid where ZOG(j) is located and divided by the number of adjacent grids; the grid with the largest gray value in the oxidation region is recorded as the boundary oxygen-displaying grid ZML, and the average gray value of the adjacent grids of ZML is recorded as ZOGs;

[0028] S502, define an integer variable k, set its initial value to 1, create two variables ZPa and ZPb with initial value of zero, and create two blank sequences Z1 and Z2 for subsequent calculation and comparison;

[0029] S503, grayscale momentum boost analysis is performed on the temperature value of the circuit where the arc sensor is located, wherein the grayscale momentum boost analysis is as follows: calculate the values ​​of ZPa and ZPb, wherein: let the value of ZPa be the absolute value of the difference between ZOG(k) and ZOF(k), let the value of ZPb be the absolute value of the difference between ZOG(k) and ZOGs; compare the values ​​of ZPa and ZPb: if ZPa is greater than ZPb, add ZOF(k) to the sequence Z1, and if ZPa is less than or equal to ZPb, add ZOF(k) to the sequence Z2;

[0030] S504, calculating the average value ZPT of all elements in the current sequence Z2, and when ZPT is less than ZP / 2, adding the smallest element in the sequence Z2 to the sequence Z1;

[0031] S505, judging whether the grayscale momentum improvement analysis is completed, the specific judging method is: if the current variable k is less than G, then k is increased by 1, and the process returns to step S503 to continue the grayscale momentum improvement analysis; if the current variable k is equal to G, then it means that the grayscale momentum improvement analysis has been processed and the process goes to step S506;

[0032] S506, recording the grids corresponding to all elements in the sequence Z1 as real oxidation grids, and recording the area consisting of all real oxidation grids and grids adjacent to the real oxidation grids as the copper foil oxidation core area.

[0033] Among them, the real oxidation grid refers to the grid formed on the surface of the copper foil due to the oxidation process, and the grayscale value is significantly lower than the normal area. They represent the most serious and significant parts of the copper foil oxidation. Compared with other grids, these grids show obvious grayscale differences and represent areas with more serious oxidation.

[0034] Among them, the copper foil oxidation core area is the most seriously oxidized area accurately extracted through advanced image analysis and grayscale momentum enhancement technology, combined with the analysis of the real oxidation grid and the adjacent grid, and the copper foil oxidation core area is the most critical part of oxidation detection; in production, the oxidation problem of copper foil will directly affect the performance and quality of the circuit board. Therefore, accurate identification and positioning of this core area are very important for subsequent maintenance, quality control, production optimization, etc. After identifying the copper foil oxidation core area, further analysis can be carried out, such as oxidation degree assessment, corrosion prediction or used to guide the adjustment of production process. At the same time, the detection of the oxidation core area can also serve as the basis for subsequent quality inspection and repair.

[0035] Furthermore, in the image, the oxidized core area of ​​the copper foil usually appears as a grayscale or color difference that is significantly different from the surrounding area, appearing as a dark or black area.

[0036] The beneficial effect of this step is: by analyzing the grayscale value ZOF(j) of the oxidized area grid and the average grayscale value ZOG(j) of the adjacent grids, two core variables ZPa and ZPb are established. These two variables reflect the difference in grayscale characteristics between the oxidized grid and its surroundings, and divide the oxidized area into two sequences Z1 and Z2, corresponding to the significant oxidation area and the area to be further analyzed: ZPa measures the overall grayscale difference between the current grid and the surrounding grids. ZPb measures the grayscale consistency of the current grid and the surrounding of the boundary oxygen-significant grid. By comparing ZPa and ZPb, grids with larger differences are preferentially classified as real oxidation grids, and other grids are temporarily stored in Z2; and by dynamically adjusting sequence Z2, abnormal grids are further screened, and the smallest element in the sequence is added to Z1. This dynamic adjustment mechanism can effectively reduce the interference of local anomalies on the analysis results. Finally, the analysis of all grids is completed, and the grids corresponding to the grayscale values ​​in sequence Z1 are identified as real oxidation grids; by comparing ZPa and ZPb, the judgment criteria are dynamically adjusted to avoid judgment deviations caused by local characteristic anomalies, and grayscale momentum boosting analysis is used to extract real oxidation features from the overall and local grayscale distributions, solving the problem in patent number CN107367465A, entitled "A method for detecting oxidation of copper foil on FPC flexible boards", that when the oxidized part of the copper foil is close to the solder resist area and the color change is not obvious, the fixed threshold judgment will miss small or complex oxidation features and texture interference, leading to misjudgment.

[0037] The beneficial effects of the present invention are: the identification process of the oxidized area is further optimized through grayscale momentum boost analysis, so that the transition area between the oxidized area and the non-oxidized area can be identified more accurately, avoiding the limitations of static threshold judgment and improving the accuracy of oxidized area detection. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 Shown is a flow chart of a defect detection method for a flexible die-cut circuit board (FDC). DETAILED DESCRIPTION

[0039] Embodiments of the present invention are described in detail below, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present invention, and should not be construed as limiting the present invention.

[0040] Figure 1 Shown is a flow chart of a defect detection method for a flexible die-cut circuit board (FDC).

[0041] Reference Figure 1 The present invention provides a defect detection method for a flexible die-cut circuit board (FDC), the method comprising the following steps:

[0042] S100, obtaining an image of the FDC circuit board to be inspected;

[0043] S200, segmenting the FDC circuit board image to be detected, identifying the copper foil area image, and extracting the copper foil area image;

[0044] S300, graying the copper foil area image to obtain a copper foil area grayscale image;

[0045] S400, calculating the oxygen grayscale value of the grayscale image of the copper foil area, and obtaining the oxidized area through the oxygen grayscale value;

[0046] S500, performing grayscale momentum boost analysis on the oxidized area, and obtaining the oxidized core area of ​​the copper foil according to the grayscale momentum boost analysis result.

[0047] According to the defect detection method of an embodiment of the present invention, the identification process of the oxidation area can be further optimized through grayscale momentum boost analysis, so that the transition area between the oxidation area and the non-oxidation area can be more accurately identified, avoiding the limitations of static threshold judgment and improving the accuracy of oxidation area detection.

[0048] Furthermore, in step S100, obtaining the image of the FDC circuit board to be inspected includes: placing the FDC circuit board to be inspected in a fixed position, adjusting the intensity of the white ring cold light source, and using a high-resolution camera to capture a colored image of the FDC circuit board to be inspected. Since the copper foil absorbs light with a wavelength less than 580nm very well, and the reflectivity of light greater than 580nm is as high as 90%, it appears red-orange. Copper oxide absorbs light with a wavelength of 400-780nm very well, so it appears black. The solder resist covering the circuit on the copper foil has an absorption rate of 70% for light with a wavelength of 620-760nm, so it appears brown and is illuminated by a white ring light, and the contrast between the three is high.

[0049] Furthermore, in step S200, the image is segmented to identify the copper foil area image. Extracting the copper foil area image includes:

[0050] The boundary is determined by the algorithm of interest, the FDC circuit board image to be inspected is segmented, and the copper foil area image is extracted.

[0051] Furthermore, in step S300, the copper foil area image is grayed out, and obtaining the copper foil area gray image includes:

[0052] The copper foil area image is grayed out, and the copper foil area image after the graying process is referred to as the copper foil area grayscale image.

[0053] Since the patent number CN107367465A, entitled "A method for detecting oxidation of copper foil of FPC flexible board", relies on color components (especially red R components) to extract oxidation areas, and judges the degree of oxidation by simple grayscale difference, this method has the problem of different color saturation or copper oxide is similar to other factors (such as solder resist, copper foil itself, etc.), it is difficult to accurately distinguish the oxidation area. In order to solve the above problem, the present invention proposes step S400;

[0054] Further, in step S400, calculating the oxygen grayscale value of the grayscale image of the copper foil area, and obtaining the oxidized area through the oxygen grayscale value includes:

[0055] The copper foil area grayscale image is grid-divided by a grid-dividing algorithm, and the grid size is one-tenth of the copper foil area grayscale image. The copper foil area grayscale image is divided into K grids, where K=1000, and s(i) represents the grayscale value of the i-th grid of the copper foil area grayscale image, i is [1, K], and K is the number of grids after the copper foil area grayscale image is divided. The median of the grayscale values ​​in each grid in s(i) is obtained and recorded as ZD, and the average of the grayscale values ​​in each grid in s(i) is obtained and recorded as ZM; the oxygen grayscale value ZP is calculated by the first equation; the oxygen grayscale value is the grayscale value for judging whether it is oxidation coloring in the grayscale difference caused by the brightness difference between the oxidation area of ​​the copper foil and the normal area under the lighting unit based on the white ring cold light source.

[0056] Among them, the method for calculating the oxygen gray value ZP in the first equation is:

[0057] Calculate the oxygen gray value ZP: subtract the absolute value of the gray range momentum from (ZM / 2), where the gray range momentum is the product of ZD and the gray momentum ratio, where the gray momentum ratio is and the ratio of (K×(ZD+ZM) / 2).

[0058] Since the grayscale value difference between the oxidized area and the normal area is generally less than half of ZM, the grayscale range momentum uses ZM / 2 as the basic grayscale, where ZD is the median of the grayscale value of the copper foil area pixel. The grayscale range momentum obtained by subtracting the grayscale of each grid and the difference between ZD and ZM from the basic grayscale ZM / 2 can effectively reduce the grayscale value impact caused by local light spots or dark spots. In the grayscale momentum ratio, (K×(ZD+ZM) / 2) is used as the denominator to reflect the momentum change of the center value of the grayscale distribution in the area. The larger the value, the more concentrated the grayscale of the area, and the more obvious the contrast between the oxidized area and the normal area. The smaller the result, the more uniform the grayscale distribution is, and a stricter oxygen grayscale value is required to distinguish the oxidized area.

[0059] The grids in s(i) whose grayscale values ​​are less than the oxygen-displaying grayscale value ZP are recorded as oxidized grids, and the area consisting of all oxidized grids in the copper foil area image is recorded as an oxidized area.

[0060] The beneficial effects of this step are: introducing dynamic adjustment of the oxygen gray value, by dynamically calculating the oxygen gray value ZP, greatly improves the sensitivity and accuracy of the oxidized area, so that the detection process of the oxidized area can adapt to different lighting conditions and scenes with color saturation changes, reduce the impact of external conditions on the detection results, refine the judgment criteria for the difference between the oxidized area and the non-oxidized area, and overcome the problem of misjudgment caused by color similarity. It avoids the decrease in detection accuracy caused by changes in color component characteristics (such as inconsistent saturation), improves the ability to extract subtle features of the oxidized area, and overcomes the confusion problem when the color of copper oxide is similar to that of the solder resist and copper foil itself.

[0061] Further, in step S500, grayscale momentum boost analysis is performed on the oxidized area, and obtaining the oxidized core area of ​​the copper foil according to the grayscale momentum boost analysis result includes:

[0062] S501, use ZOF(j) to represent the grayscale value of the grid of the jth oxidation region, the value range of the serial number j is [1, G], where G is the number of grids in the oxidation region; ZOG(j) represents the average grayscale value of the adjacent grids of the jth oxidation region grid.

[0063] Furthermore, the adjacent grid refers to the grid that shares the border with the current grid, wherein the gray value of the grid is the average gray value of all pixels in the grid, wherein the average gray value of the adjacent grids of the jth oxidation region grid is the sum of the gray values ​​of all adjacent grids of the grid where ZOG(j) is located and divided by the number of adjacent grids; the grid with the largest gray value in the oxidation region is recorded as the boundary oxygen-displaying grid ZML, and the average gray value of the adjacent grids of ZML is recorded as ZOGs;

[0064] S502, define an integer variable k, set its initial value to 1, create two variables ZPa and ZPb with initial value of zero, and create two blank sequences Z1 and Z2 for subsequent calculation and comparison;

[0065] S503, performing grayscale momentum boost analysis on the temperature value of the circuit where the arc sensor is located, wherein the grayscale momentum boost analysis is: calculating the values ​​of ZPa and ZPb, wherein: setting the value of ZPa to the absolute value of the difference between ZOG(k) and ZOF(k), setting the value of ZPb to the absolute value of the difference between ZOG(k) and ZOGs;

[0066] Compare the values ​​of ZPa and ZPb: if ZPa is greater than ZPb, add ZOF(k) to sequence Z1; if ZPa is less than or equal to ZPb, add ZOF(k) to sequence Z2;

[0067] S504, calculating the average value ZPT of all elements in the current sequence Z2, and when ZPT is less than ZP / 2, adding the smallest element in the sequence Z2 to the sequence Z1;

[0068] S505, judging whether the grayscale momentum improvement analysis is completed, the specific judging method is: if the current variable k is less than G, then k is increased by 1, and the process returns to step S503 to continue the grayscale momentum improvement analysis; if the current variable k is equal to G, then it means that the grayscale momentum improvement analysis has been processed and the process goes to step S506;

[0069] S506, recording the grids corresponding to all elements in the sequence Z1 as real oxidation grids, and recording the area consisting of all real oxidation grids and grids adjacent to the real oxidation grids as the copper foil oxidation core area.

[0070] Among them, the real oxidation grid refers to the grid formed on the surface of the copper foil due to the oxidation process, and the grayscale value is significantly lower than the normal area. They represent the most serious and significant parts of the copper foil oxidation. Compared with other grids, these grids show obvious grayscale differences and represent areas with more serious oxidation.

[0071] Among them, the copper foil oxidation core area is the most seriously oxidized area accurately extracted through advanced image analysis and grayscale momentum enhancement technology, combined with the analysis of the real oxidation grid and the adjacent grid, and the copper foil oxidation core area is the most critical part of oxidation detection; in production, the oxidation problem of copper foil will directly affect the performance and quality of the circuit board. Therefore, accurate identification and positioning of this core area are very important for subsequent maintenance, quality control, production optimization, etc. After identifying the copper foil oxidation core area, further analysis can be carried out, such as oxidation degree assessment, corrosion prediction or used to guide the adjustment of production process. At the same time, the detection of the oxidation core area can also serve as the basis for subsequent quality inspection and repair.

[0072] Furthermore, in the image, the oxidized core area of ​​the copper foil usually appears as a grayscale or color difference that is significantly different from the surrounding area, appearing as a dark or black area.

[0073] The beneficial effect of this step is: by analyzing the grayscale value ZOF(j) of the oxidized area grid and the average grayscale value ZOG(j) of the adjacent grids, two core variables ZPa and ZPb are established. These two variables reflect the difference in grayscale characteristics between the oxidized grid and its surroundings, and divide the oxidized area into two sequences Z1 and Z2, corresponding to the significant oxidation area and the area to be further analyzed: ZPa measures the overall grayscale difference between the current grid and the surrounding grids. ZPb measures the grayscale consistency of the current grid and the surrounding of the boundary oxygen-significant grid. By comparing ZPa and ZPb, grids with larger differences are preferentially classified as real oxidation grids, and other grids are temporarily stored in Z2; and abnormal grids are further screened by dynamically adjusting sequence Z2, and the smallest element in the sequence is added to Z1. This dynamic adjustment mechanism can effectively reduce the interference of local anomalies on the analysis results. Finally, the analysis of all grids is completed, and the grids corresponding to the grayscale values ​​in sequence Z1 are identified as real oxidation grids; by comparing ZPa and ZPb, the judgment criteria are dynamically adjusted to avoid judgment deviations caused by local characteristic anomalies, and grayscale momentum lifting analysis is used to extract the real oxidation features from the overall and local grayscale distributions, solving the problem in the patent number CN107367465A entitled "A method for detecting oxidation of copper foil of FPC flexible board", that when the oxidized part of the copper foil is close to the solder resist area and the color change is not obvious, the fixed threshold judgment will miss small or complex oxidation features and texture interference, resulting in misjudgment; through grid analysis, combined with a dynamic screening mechanism, the oxidation core area is gradually extracted, and the oxidized part is accurately separated from the larger oxidation area, which can achieve a higher level of regional refinement.

[0074] The beneficial effects of the present invention are: the identification process of the oxidized area is further optimized through grayscale momentum boost analysis, so that the transition area between the oxidized area and the non-oxidized area can be identified more accurately, avoiding the limitations of static threshold judgment and improving the accuracy of oxidized area detection.

[0075] It should be noted that the logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be specifically implemented in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in combination with these instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in combination with these instruction execution systems, devices or apparatuses. More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection portion with one or more wirings (electronic device), a portable computer disk box (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium and then editing, interpreting or processing in other suitable ways if necessary, and then stored in a computer memory.

[0076] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, a plurality of steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0077] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "examples", "specific examples", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0078] In the description of the present invention, it is to be understood that the terms “center”, “longitudinal”, “lateral”, “length”, “width”, “thickness”, “up”, “down”, “front”, “back”, “left”, “right”, “vertical”, “horizontal”, “top”, “bottom”, “inside”, “outside”, “clockwise”, “counterclockwise”, “axial”, “radial”, “circumferential”, etc., indicating orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings, are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the referred device or element must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as limiting the present invention.

[0079] In addition, the terms "first", "second", etc. used in the embodiments of the present invention are only used for descriptive purposes and should not be understood as indicating or implying relative importance, or implicitly indicating the number of technical features indicated in the present embodiment. Therefore, the features defined by the terms "first", "second", etc. in the embodiments of the present invention can explicitly or implicitly indicate that the embodiment includes at least one of the features. In the description of the present invention, the word "multiple" means at least two or two or more, such as two, three, four, etc., unless otherwise clearly and specifically defined in the embodiments.

[0080] In the present invention, unless otherwise clearly specified or limited in the embodiments, the terms "installed", "connected", "connected" and "fixed" etc. in the embodiments should be understood in a broad sense. For example, the connection can be a fixed connection, a detachable connection, or an integrated connection. It can be understood that it can also be a mechanical connection, an electrical connection, etc.; of course, it can also be a direct connection, or an indirect connection through an intermediate medium, or it can be the internal connection of two elements, or the interaction relationship between two elements. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to the specific implementation situation.

[0081] In the present invention, unless otherwise clearly specified and limited, a first feature being "above" or "below" a second feature may mean that the first and second features are in direct contact, or the first and second features are in indirect contact through an intermediate medium. Moreover, a first feature being "above", "above" or "above" a second feature may mean that the first feature is directly above or obliquely above the second feature, or simply means that the first feature is higher in level than the second feature. A first feature being "below", "below" or "below" a second feature may mean that the first feature is directly below or obliquely below the second feature, or simply means that the first feature is lower in level than the second feature.

[0082] Although the embodiments of the present invention have been shown and described above, it is to be understood that the above embodiments are exemplary and are not to be construed as limitations of the present invention. A person skilled in the art may change, modify, replace and vary the above embodiments within the scope of the present invention.

Claims

1. A defect detection method for a flexible die-cut circuit board (FDC), characterized in that: The method comprises the following steps: S100, obtaining an image of the FDC circuit board to be inspected; S200, segmenting the FDC circuit board image to be detected, identifying the copper foil area image, and extracting the copper foil area image; S300, graying the copper foil area image to obtain a copper foil area grayscale image; S400, calculating the oxygen grayscale value of the grayscale image of the copper foil area, and obtaining the oxidized area through the oxygen grayscale value; S500, performing grayscale momentum boost analysis on the oxidized area, and obtaining the oxidized core area of ​​the copper foil according to the grayscale momentum boost analysis result.

2. A defect detection method for a flexible die-cut circuit board (FDC) according to claim 1, characterized in that: In step S200, the image is segmented to identify the copper foil area image. Extracting the copper foil area image includes: The boundary is determined by the algorithm of interest, the FDC circuit board image to be inspected is segmented, and the copper foil area image is extracted.

3. A defect detection method for a flexible die-cut circuit board (FDC) according to claim 1, characterized in that: In step S300, the copper foil area image is grayed out, and obtaining the copper foil area gray image includes: The copper foil area image is grayed out, and the copper foil area image after the graying process is referred to as the copper foil area grayscale image.

4. A defect detection method for a flexible die-cut circuit board (FDC) according to claim 3, characterized in that: In step S400, calculating the oxygen grayscale value of the grayscale image of the copper foil area, and obtaining the oxidized area through the oxygen grayscale value includes: The copper foil area grayscale image is grid-divided by a grid division algorithm, and the grid size is one-tenth of the copper foil area grayscale image. The copper foil area grayscale image is divided into K grids, where K = 1000, s(i) represents the grayscale value of the i-th grid of the copper foil area grayscale image, the value of i is [1, K], and K is the number of grids after the copper foil area grayscale image is divided; the median of the grayscale values ​​in each grid in s(i) is obtained and recorded as ZD, and the average value of the grayscale values ​​in each grid in s(i) is obtained and recorded as ZM The oxygen gray value ZP is calculated by the first equation; wherein the oxygen gray value is a gray value for judging whether it is oxidation coloration in the gray difference caused by the brightness difference between the oxidation area of ​​the copper foil and the normal area under the lighting unit based on the white ring cold light source; Among them, the method for calculating the oxygen gray value ZP in the first equation is: Calculate the oxygen gray value ZP by subtracting the absolute value of the gray range momentum from (ZM / 2), where the gray range momentum is the product of ZD and the gray momentum ratio; The grids in s(i) whose grayscale values ​​are less than the oxygen-displaying grayscale value ZP are recorded as oxidized grids, and the area consisting of all oxidized grids in the copper foil area image is recorded as an oxidized area.

5. A defect detection method for a flexible die-cut circuit board (FDC) according to claim 4, characterized in that: In step S500, grayscale momentum boost analysis is performed on the oxidized area, and obtaining the oxidized core area of ​​the copper foil according to the grayscale momentum boost analysis result includes: S501, use ZOF(j) to represent the grayscale value of the grid of the jth oxidation area, the value range of the serial number j is [1, G], where G is the number of grids in the oxidation area; ZOG(j) represents the average value of the grayscale values ​​of the adjacent grids of the jth oxidation area grid; the adjacent grid refers to the grid that shares a boundary with the current grid, wherein the grayscale value of the grid is the average value of the grayscale values ​​of all pixels in the grid, wherein the average value of the grayscale values ​​of the adjacent grids of the jth oxidation area grid is the sum of the grayscale values ​​of all adjacent grids of the grid where ZOG(j) is located and divided by the number of adjacent grids; the grid with the largest grayscale value in the oxidation area is recorded as the boundary oxygen-displaying grid ZML, and the average value of the grayscale values ​​of the adjacent grids of ZML is recorded as ZOGs; S502, define an integer variable k, set its initial value to 1, create two variables ZPa and ZPb with initial value of zero, and create two blank sequences Z1 and Z2 for subsequent calculation and comparison; S503, grayscale momentum boost analysis is performed on the temperature value of the circuit where the arc sensor is located, wherein the grayscale momentum boost analysis is as follows: calculate the values ​​of ZPa and ZPb, wherein: let the value of ZPa be the absolute value of the difference between ZOG(k)-ZOF(k), let the value of ZPb be the absolute value of the difference between ZOG(k) and ZOGs; compare the values ​​of ZPa and ZPb: if ZPa is greater than ZPb, then add ZOF(k) to sequence Z1; if ZPa is less than or equal to ZPb, then add ZOF(k) to sequence Z2, S504, calculating the average value ZPT of all elements in the current sequence Z2, and when ZPT is less than ZP / 2, adding the smallest element in the sequence Z2 to the sequence Z1; S505, judging whether the grayscale momentum improvement analysis is completed, the specific judging method is: if the current variable k is less than G, then k is increased by 1, and the process returns to step S503 to continue the grayscale momentum improvement analysis; if the current variable k is equal to G, then the grayscale momentum improvement analysis has been completed and the process goes to step S506; S506, recording the grids corresponding to all elements in the sequence Z1 as real oxidation grids, and recording the area consisting of all real oxidation grids and grids adjacent to the real oxidation grids as the copper foil oxidation core area.

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