Cut-stack equipment CCD (Charge Coupled Device) size calibration point inspection method, system, equipment and medium

Abstract

The invention relates to a cutting and stacking device CCD size calibration point inspection method, system and device and a medium, and is applied to the technical field of battery cutting and stacking device calibration. The method comprises the steps that a calibration plate image which is shot by a target CCD camera and comprises a checkerboard area is acquired; determining angular point coordinates of the checkerboard area in the calibration board image based on a preset function; performing distortion correction on the calibration plate image based on the angular point coordinates to generate a corrected calibration plate image; performing checkerboard area division on a checkerboard area in the correction calibration board image to generate a checkerboard area division result; pixel point extraction is carried out on the chessboard region division result, and identification pixel points of the correction calibration board image are determined; and obtaining a comparison reference value, and generating a benchmark point inspection result based on the comparison reference value and the standard pixel points. The method and the device have the effect of quickly and accurately realizing the punctuation point inspection of the target CCD camera.

Description

Technical Field

[0001] The present application relates to the technical field of battery cutting and stacking equipment calibration, and in particular to a method, system, equipment and medium for CCD size calibration inspection of cutting and stacking equipment. Background Art

[0002] Target CCD cameras have been widely used in various industries, such as positioning, dimension measurement and product deviation monitoring, especially in the lithium battery industry, where target CCD cameras play an important role in parameter measurement. For example, in the pole piece size and overhang of cutting and stacking equipment, these parameters will directly affect the quality of the product. However, the accuracy of the target CCD camera used for parameter calculation will be affected to a certain extent during operation due to machine jitter and manual maintenance and debugging. Therefore, the alignment and calibration of the target CCD camera has become a high-frequency task.

[0003] At present, the calibration of CCD mainly adopts Zhang Zhengyou's chessboard calibration method, and the calibration is carried out by comparing the target CCD camera with the data measured by the second element. At present, in the field of civil engineering, the displacement of the foundation pit is calculated by the offset of the corner coordinates of the chessboard in the foundation pit through image recognition, but this method is mainly aimed at real-time monitoring of engineering foundation pits with large working spaces. However, since the working space of the target CCD camera in the cutting and stacking equipment is relatively small, the existing method cannot be perfectly applied. There is an urgent need for a technology that can quickly and accurately realize the calibration and inspection of the target CCD camera. Summary of the invention

[0004] In order to quickly and accurately realize the target CCD camera alignment inspection, the present application provides a cutting and stacking equipment CCD size alignment inspection method, system, equipment and medium.

[0005] In the first aspect, the present application provides a CCD size calibration inspection method for a cutting and stacking device, which adopts the following technical solution:

[0006] A CCD size calibration inspection method for cutting and stacking equipment, comprising:

[0007] Obtain a calibration plate image containing a checkerboard area captured by a target CCD camera;

[0008] Determine the coordinates of the corner points of the checkerboard area in the calibration plate image based on a preset function;

[0009] Performing distortion correction on the calibration plate image based on the corner point coordinates to generate a corrected calibration plate image;

[0010] Performing chessboard area division on the chessboard area in the calibration plate image to generate a chessboard area division result;

[0011] Extracting pixels from the chessboard area division result to determine the identification pixels of the calibration plate image;

[0012] A comparison reference value is obtained, and a calibration point inspection result is generated based on the comparison reference value and the standard pixel point.

[0013] By adopting the above technical scheme, a target CCD camera is used to shoot a calibration plate including a checkerboard area to obtain a calibration plate image. After determining the coordinates of the corner points of the checkerboard area in the calibration plate image, the captured calibration plate image is subjected to distortion correction according to the corner point coordinates to obtain a corrected calibration plate image, so as to eliminate the distortion generated during shooting and improve the accuracy of subsequent alignment inspection. The corrected calibration plate image is divided into checkerboard areas to obtain a checkerboard area division result, and identification pixel points are extracted based on the checkerboard area division result. The final alignment inspection result is determined using the extracted identification pixel points and the avoidance reference value. The entire inspection process is performed automatically without the need for manual timed inspection, thereby enabling the target CCD camera alignment inspection to be quickly and accurately achieved.

[0014] Optionally, determining the coordinates of corner points of the checkerboard area in the calibration plate image based on a preset function includes:

[0015] Obtaining a region corner point identifier, and determining a region corner point of the checkerboard region based on the preset function and the region corner point identifier;

[0016] Based on the preset function, corner point sub-pixel extraction is performed on the corner points of the area to obtain the coordinates of the corner points of the chessboard area.

[0017] Optionally, the performing distortion correction on the calibration plate image based on the corner point coordinates to generate a corrected calibration plate image includes:

[0018] Acquire the image coordinate system of the corner point coordinates and the camera position information of the target CCD camera;

[0019] Constructing a standard physical coordinate system based on the camera position information;

[0020] Determine a coordinate correspondence relationship based on the image coordinate system and the standard physical coordinate system;

[0021] Calculating the distortion coefficient of the target CCD camera based on the coordinate correspondence and the corner point coordinates;

[0022] The calibration plate image is subjected to distortion correction based on the distortion coefficient to generate a corrected calibration plate image.

[0023] Optionally, performing chessboard area division on the chessboard area in the calibration plate image to generate a chessboard area division result includes:

[0024] Performing feature recognition on the calibration plate image based on a preset neural network to generate a recognition result;

[0025] The recognition result is selected through a region candidate network to generate a region recognition result;

[0026] Get the chessboard area information;

[0027] The checkerboard area division is performed on the calibration layout based on the checkerboard area information and the area recognition result to generate a checkerboard area division result.

[0028] Optionally, the extracting pixels from the chessboard area division result to determine the identification pixels of the calibration plate image includes:

[0029] Get pixel extraction target information;

[0030] Determine a target pixel extraction point based on the pixel extraction target information and the chessboard area division result;

[0031] Pixel points are extracted from the chessboard area division result based on the target pixel extraction points to obtain the identification pixel points of the correction calibration plate image.

[0032] Optionally, generating a calibration point inspection result based on the comparison reference value and the standard pixel point includes:

[0033] Obtaining a calculation rule for the comparison benchmark value;

[0034] Calculate the pixel spacing of the standard pixel points based on the calculation rule to generate a spacing calculation result;

[0035] Calculate the offset difference based on the spacing calculation result and the comparison reference value;

[0036] Get the anomaly threshold;

[0037] A calibration inspection result is generated based on the offset difference and the abnormality threshold.

[0038] Optionally, generating the alignment inspection result based on the offset difference and the abnormal threshold includes:

[0039] Calculate the offset average value based on the offset difference;

[0040] Determine whether the abnormal threshold is greater than or equal to the deviation average value;

[0041] If the abnormal threshold is greater than or equal to the deviation average value, the alignment inspection result is classified as a qualified state;

[0042] If the abnormal threshold is less than the deviation average value, the alignment inspection result is classified as unqualified.

[0043] In the second aspect, the present application provides a CCD size calibration inspection system for cutting and stacking equipment, which adopts the following technical solution:

[0044] A CCD size calibration inspection system for cutting and stacking equipment, comprising:

[0045] A calibration image acquisition module is used to acquire a calibration plate image containing a checkerboard area captured by a target CCD camera;

[0046] A corner point coordinate determination module, used to determine the corner point coordinates of the checkerboard area in the calibration plate image based on a preset function;

[0047] A correction calibration plate image generation module, used for performing distortion correction on the calibration plate image based on the corner point coordinates to generate a correction calibration plate image;

[0048] A chessboard result generation module, used to perform chessboard area division on the chessboard area in the calibration plate image and generate a chessboard area division result;

[0049] A marking pixel determination module is used to extract pixel points from the chessboard area division result to determine the marking pixel points of the calibration plate image;

[0050] The spot inspection result generating module is used to obtain a comparison reference value, and generate a calibration spot inspection result based on the comparison reference value and the standard pixel point.

[0051] By adopting the above technical scheme, a target CCD camera is used to shoot a calibration plate including a checkerboard area to obtain a calibration plate image. After determining the coordinates of the corner points of the checkerboard area in the calibration plate image, the captured calibration plate image is subjected to distortion correction according to the corner point coordinates to obtain a corrected calibration plate image, so as to eliminate the distortion generated during shooting and improve the accuracy of subsequent alignment inspection. The corrected calibration plate image is divided into checkerboard areas to obtain a checkerboard area division result, and identification pixel points are extracted based on the checkerboard area division result. The final alignment inspection result is determined using the extracted identification pixel points and the avoidance reference value. The entire inspection process is performed automatically without the need for manual timed inspection, thereby enabling the target CCD camera alignment inspection to be quickly and accurately achieved.

[0052] In a third aspect, the present application provides an electronic device, which adopts the following technical solution:

[0053] An electronic device comprises a processor, wherein the processor is coupled to a memory;

[0054] The processor is used to execute the computer program stored in the memory, so that the electronic device executes the computer program of the CCD size alignment and inspection method of the cutting and stacking device described in any one of the first aspects.

[0055] In a fourth aspect, the present application provides a computer-readable storage medium, which adopts the following technical solution:

[0056] A computer-readable storage medium stores a computer program that can be loaded by a processor and execute the CCD size alignment and inspection method for cutting and stacking equipment described in any one of the first aspects.

[0057] In summary, the present application includes at least one of the following beneficial technical effects:

[0058] A target CCD camera is used to shoot a calibration plate including a chessboard area to obtain a calibration plate image. After determining the coordinates of the corner points of the chessboard area in the calibration plate image, the calibration plate image is subjected to distortion correction according to the corner point coordinates to obtain a corrected calibration plate image, so as to eliminate the distortion generated during shooting and improve the accuracy of subsequent alignment inspection. The corrected calibration plate image is divided into chessboard areas to obtain a chessboard area division result, and identification pixel points are extracted based on the chessboard area division result. The final alignment inspection result is determined using the extracted identification pixel points and the avoidance reference value. The entire inspection process is performed automatically without the need for manual inspection at a fixed time, thereby enabling the target CCD camera alignment inspection to be achieved quickly and accurately. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] Figure 1 It is a flow chart of a CCD size calibration inspection method for a cutting and stacking device provided in an embodiment of the present application.

[0060] Figure 2 It is a structural schematic diagram of the position of the newly added calibration plate of the segment manufacturing method provided in the embodiment of the present application.

[0061] Figure 3 It is a structural schematic diagram of the position of the newly added calibration plate of the stacked segment provided in an embodiment of the present application.

[0062] Figure 4 It is a structural schematic diagram of the chessboard image shooting division provided in an embodiment of the present application.

[0063] Figure 5 It is a structural schematic diagram of the chessboard area division result provided in an embodiment of the present application.

[0064] Figure 6 It is a structural block diagram of a CCD size alignment and inspection system for cutting and stacking equipment provided in an embodiment of the present application.

[0065] Figure 7It is a structural block diagram of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0066] The present application is further described in detail below in conjunction with the accompanying drawings.

[0067] The embodiment of the present application provides a CCD size calibration and inspection method for a stacking device, which can be executed by an electronic device, which can be a server or a terminal device, wherein the server can be an independent physical server, or a server cluster or distributed system composed of multiple physical servers, or a cloud server providing cloud computing services. The terminal device can be a smart phone, a tablet computer, a desktop computer, etc., but is not limited thereto.

[0068] Figure 1 A schematic flow chart of a CCD size calibration inspection method for a cutting and stacking device provided in an embodiment of the present application.

[0069] like Figure 1 As shown, the main process of the method is described as follows (steps S101 to S106):

[0070] Step S101, obtaining a calibration plate image including a checkerboard area captured by a target CCD camera.

[0071] In this embodiment, a calibration plate with a European black and white checkerboard is added to the existing cutting and stacking equipment, such as Figure 2 and Figure 3 As shown, black and white checkerboard calibration plates are added to the made segment and the stacked segment respectively, wherein 1 is the pole piece, 2 is the four checkerboard calibration plates fixed on the bottom plate of the made segment, 3 is the bottom plate of the made segment, 4 is the stacking press knife, 5 is the stacking table, and 6 is the four checkerboard calibration plates fixed on the stacking table press knife of the stacked segment. When shooting, it is necessary to shoot the made segment and the stacked segment respectively. When performing calibration inspection, it is necessary to execute the overall step flow for the calibration plate image shot by the made segment, and it is also necessary to execute the overall step flow for the calibration plate image shot by the stacked segment. Since the executed step flow is consistent, a unified description is given here without repeated descriptions.

[0072] The target CCD camera is the target CCD camera used for normal operation. The target CCD camera periodically captures images of the prepared segments and the overlapped segments to obtain a calibration plate image containing 4 checkerboard calibration plates. The CCD size calibration point check is performed based on the captured calibration plate image. When shooting, the specific shooting field of view refers to Figure 4 , where 7 is the target CCD camera, 8 is the checkerboard calibration plate, 9 is the target CCD camera field of view, and 10 is the corner points and identification pixels that need to be extracted. In the subsequent processing, Figure 4The image of the calibration plate captured in the schematic field of view is processed and analyzed to determine several key position points circled at position 10.

[0073] In this embodiment, when capturing the image of the calibration plate, the staff can manually control it according to the actual calibration inspection needs, and can also set an automatic program according to the actual calibration inspection needs, that is, when calibration inspection is required, the staff manually controls the target CCD camera to capture the image of the calibration plate and starts to execute the overall step process, or sets the shooting time. When the shooting time is reached, the program automatically controls the target CCD camera to capture the image of the calibration plate and starts to execute the overall step process. The shooting time can be set to a fixed time every day, a fixed time every week, or a fixed time interval, etc., which is not specifically limited here.

[0074] Step S102, determining the coordinates of the corner points of the checkerboard area in the calibration plate image based on a preset function.

[0075] For step S102, obtain the regional corner point identifier, determine the regional corner points of the chessboard area based on the preset function and the regional corner point identifier; perform corner point sub-pixel extraction on the regional corner points based on the preset function to obtain the corner point coordinates of the chessboard area.

[0076] In this embodiment, the center point of the chessboard area is used as the regional corner point, so that the regional corner point identifier is set as the vertex intersection of the four squares of the chessboard. After obtaining the regional corner point identifier, the regional corner point is determined on the chessboard area according to the preset function and the regional corner point identifier. Specifically, the regional corner points in the chessboard area are found through the findChessboardCorners function and the regional corner point identifier in Opencv. After finding the regional corner points of the four chessboard areas in the calibration plate image, the preset function is called to perform corner sub-pixel extraction on the regional corner points to obtain the corner point coordinates of the regional corner points. Specifically, cornerSubPix() is called to perform corner sub-pixel extraction on the regional corner points, and the precise coordinates of the regional corner points are output.

[0077] It should be noted that the determination of the regional corner points and the determination of the corner point coordinates both obtain four data. Since there are four checkerboard areas in the calibration plate image, when extracting and determining the regional corner points and corner point coordinates, each checkerboard area needs to perform the same steps to obtain the four regional corner points and the corner point coordinates corresponding to the fish area corner points.

[0078] Step S103, performing distortion correction on the calibration plate image based on the corner point coordinates to generate a corrected calibration plate image.

[0079] For step S103, obtain the image coordinate system of the corner point coordinates and the camera position information of the target CCD camera; construct a standard physical coordinate system based on the camera position information; determine the coordinate correspondence based on the image coordinate system and the standard physical coordinate system; calculate the distortion coefficient of the target CCD camera based on the coordinate correspondence and the corner point coordinates; perform distortion correction on the calibration plate image based on the distortion coefficient to generate a corrected calibration plate image.

[0080] In this embodiment, the image coordinate system of the corner point coordinates includes the coordinate origin, xyz axis direction, etc. of the corner point coordinates, and then a standard physical coordinate system is constructed according to the camera position information of the target CCD camera, and a conversion relationship is determined according to the scaling relationship between the standard physical coordinate system and the image coordinate system, internal and external parameters of the target CCD, and other information, and the correspondence between the two coordinate systems is determined according to the conversion relationship, and then the distortion coefficient of the target CCD camera is calculated using a nonlinear optimization algorithm and the corner point coordinates and the corresponding relationship to obtain the final distortion coefficient, and the calibration plate image is subjected to distortion correction processing using the calculated distortion coefficient to eliminate the distortion effect and obtain a corrected calibration plate image for subsequent use.

[0081] Step S104, performing chessboard area division on the chessboard area in the calibration plate image to generate a chessboard area division result.

[0082] For step S104, feature recognition is performed on the calibration plate image based on a preset neural network to generate a recognition result; the recognition result is subjected to region recognition and selection through a region candidate network to generate a region recognition result; checkerboard region information is obtained; based on the checkerboard region information and the region recognition result, the calibration plate is divided into checkerboard regions to generate a checkerboard region division result.

[0083] In this embodiment, the calibration plate image is input into the CNN convolutional neural network for checkerboard feature recognition. After passing through the convolution layer of the convolutional neural network, an output value f, i.e., the recognition result, is obtained. The output value f is passed through the RPN (Region Proposal Network) for region selection, i.e., the recognition result is selected through the region candidate network for region recognition to obtain the final region recognition result. The recognition result is segmented through the checkerboard region information and Segmentation Network segmentation to obtain the following: Figure 5 The area division result shown, wherein the chessboard area information includes the number of black and white squares in the chessboard and the distribution method of the black and white squares.

[0084] Step S105, extracting pixels from the chessboard area division result to determine the identification pixels of the calibration plate image.

[0085] For step S105, pixel extraction target information is obtained; based on the pixel extraction target information and the chessboard area division result, a target pixel extraction point is determined; based on the target pixel extraction point, pixel points of the chessboard area division result are extracted to obtain identification pixel points of the correction calibration plate image.

[0086] In this embodiment, the pixel extraction information is the location information for pixel extraction. Figure 4 For example, the pixel extraction information is the center point of each chessboard area division result in the chessboard. The center point position is determined in the chessboard area division result according to the pixel extraction information. After the center point position is determined, the determined position is used as the target pixel extraction point, and pixel point extraction is performed on the target pixel extraction point to obtain the identification pixel point of the correction calibration plate image.

[0087] Step S106, obtaining a comparison reference value, and generating a calibration point inspection result based on the comparison reference value and the standard pixel point.

[0088] For step S106, obtain the calculation rules of the comparison benchmark value; calculate the pixel spacing of the standard pixel points based on the calculation rules to generate a spacing calculation result; calculate the offset difference based on the spacing calculation result and the comparison benchmark value; obtain the abnormality threshold; generate the alignment point inspection result based on the offset difference and the abnormality threshold.

[0089] In this embodiment, the comparison reference value is the data collected under the most standard state after the initial manual adjustment is completed. In subsequent use, the size of the target CCD camera needs to be in a standard state, so that the data collected under the most standard state is used as the comparison reference value. In the subsequent calibration inspection, the comparison and adjustment are performed based on the comparison reference value.

[0090] First, determine the calculation rule of the comparison benchmark value. The calculation rule is to calculate the one-to-one correspondence between the pixels at the same position, and then calculate the distance between the same pixels. Figure 1 and Figure 5 There are four chessboard area division results in each calibration plate image, which are recorded as ABCD. Each chessboard area division result has four positions 1234. When calculating the pixel spacing, the spacing between the pixels at the same position 1 in the A chessboard grid and the BCD chessboard grid is calculated, and so on. After the spacing of all positions of all chessboard area division results is calculated, the calculation is completed, and the value calculated based on the data collected under the most standard state is used as the comparison benchmark value.

[0091] The pixel spacing of the marked pixels is calculated using the calculation rules to obtain multiple spacing values. All the spacing values ​​are used as the spacing calculation results. The spacing calculation results and the comparison benchmark values ​​are matched one by one according to the calculation chessboard area division results and positions. Then, the difference between the corresponding spacing calculation results and the comparison benchmark values ​​is calculated, and the difference is used as the offset difference. The alignment inspection results are generated according to the offset difference and the abnormal threshold.

[0092] The specific method of generating the alignment inspection result according to the offset difference and the abnormality threshold is as follows: the offset average value is calculated based on the offset difference; whether the abnormality threshold is greater than or equal to the offset average value is determined; if the abnormality threshold is greater than or equal to the offset average value, the alignment inspection result is classified as a qualified state; if the abnormality threshold is less than the offset average value, the alignment inspection result is classified as an unqualified state.

[0093] In this embodiment, an abnormality threshold set according to the process standard is obtained, and the average value calculated by the offset difference is used as the offset average value. The abnormality threshold is compared with the offset average value. When the abnormality threshold is greater than or equal to the offset average value, the alignment inspection result is classified as a qualified state, and the output is marked as a qualified result. Conversely, when the abnormality threshold is less than the offset average value, the alignment inspection result is classified as an unqualified state, and the output is marked as an unqualified result. The offset average value is stored in the local log of the system, and a compensation value is calculated at the same time. The alignment inspection process is automatically performed according to the compensation value to ensure the detection accuracy of the target CCD camera, wherein the compensation value is the absolute value of the difference between the offset average value and the abnormality threshold.

[0094] Figure 2 A structural block diagram of a CCD size alignment inspection system 200 for cutting and stacking equipment provided in an embodiment of the application.

[0095] like Figure 2 As shown, the CCD size calibration and inspection system 200 for cutting and stacking equipment mainly includes:

[0096] The calibration image acquisition module 201 is used to acquire a calibration plate image including a checkerboard area captured by a target CCD camera;

[0097] A corner point coordinate determination module 202 is used to determine the corner point coordinates of the checkerboard area in the calibration plate image based on a preset function;

[0098] The calibration plate image correction generation module 203 is used to perform distortion correction on the calibration plate image based on the corner point coordinates to generate a calibration plate image correction;

[0099] A chessboard result generating module 204 is used to perform chessboard area division on the chessboard area in the calibration plate image and generate a chessboard area division result;

[0100] The identification pixel determination module 205 is used to extract pixel points from the chessboard area division result and determine the identification pixel points of the calibration plate image;

[0101] The spot inspection result generating module 206 is used to obtain a comparison reference value, and generate a calibration spot inspection result based on the comparison reference value and the standard pixel point.

[0102] As an optional implementation of this embodiment, the corner point coordinate determination module 202 is specifically used to obtain the regional corner point identifier, determine the regional corner points of the checkerboard area based on a preset function and the regional corner point identifier; perform corner point sub-pixel extraction on the regional corner points based on the preset function to obtain the corner point coordinates of the checkerboard area.

[0103] As an optional implementation manner of this embodiment, the correction calibration plate image generation module 203 is specifically used to obtain the image coordinate system of the corner point coordinates and the camera position information of the target CCD camera; construct a standard physical coordinate system based on the camera position information; determine the coordinate correspondence based on the image coordinate system and the standard physical coordinate system; calculate the distortion coefficient of the target CCD camera based on the coordinate correspondence and the corner point coordinates; perform distortion correction on the calibration plate image based on the distortion coefficient to generate a correction calibration plate image.

[0104] As an optional implementation of this embodiment, the chessboard result generation module 204 is specifically used to perform feature recognition on the correction and calibration plate image based on a preset neural network to generate a recognition result; the recognition result is selected through a region candidate network to generate a region recognition result; obtain chessboard region information; divide the correction and calibration layout into chessboard regions based on the chessboard region information and the region recognition result to generate a chessboard region division result.

[0105] As an optional implementation of this embodiment, the identification pixel determination module 205 is specifically used to obtain pixel extraction target information; determine the target pixel extraction point based on the pixel extraction target information and the chessboard area division result; extract pixel points of the chessboard area division result based on the target pixel extraction point to obtain the identification pixel points of the correction calibration plate image.

[0106] As an optional implementation of this embodiment, the inspection result generating module 206 includes:

[0107] A calculation rule acquisition module is used to obtain the calculation rule of the comparison benchmark value;

[0108] A calculation result generation module is used to calculate the pixel spacing of standard pixel points based on the calculation rules and generate the spacing calculation result;

[0109] An offset difference calculation module is used to calculate the offset difference based on the spacing calculation result and the comparison reference value;

[0110] An abnormal threshold acquisition module, used to obtain an abnormal threshold;

[0111] The calibration result generation module is used to generate calibration results based on the offset difference and the abnormality threshold.

[0112] In this optional embodiment, the calibration inspection result generation module is specifically used to calculate the offset average value based on the offset difference; determine whether the abnormality threshold is greater than or equal to the offset average value; if the abnormality threshold is greater than or equal to the offset average value, the calibration inspection result is classified as a qualified state; if the abnormality threshold is less than the offset average value, the calibration inspection result is classified as an unqualified state.

[0113] In one example, the module in any of the above devices can be one or more integrated circuits configured to implement the above methods, such as: one or more application specific integrated circuits (ASICs), or, one or more digital signal processors (DSPs), or, one or more field programmable gate arrays (FPGAs), or a combination of at least two of these integrated circuit forms.

[0114] For another example, when the modules in the device can be implemented in the form of a processing element scheduling program, the processing element can be a general-purpose processor, such as a central processing unit (CPU) or other processor that can call a program. For another example, these modules can be integrated together and implemented in the form of a system-on-a-chip (SOC).

[0115] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described devices and modules can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0116] Figure 3 This is a structural block diagram of an electronic device 300 provided in an embodiment of the present application.

[0117] like Figure 3 As shown, the electronic device 300 includes a processor 301 and a memory 302 , and may further include an information input / information output (I / O) interface 303 , one or more of a communication component 304 , and a communication bus 305 .

[0118] The processor 301 is used to control the overall operation of the electronic device 300 to complete all or part of the steps of the CCD size calibration inspection method for the stacking device; the memory 302 is used to store various types of data to support the operation of the electronic device 300, and these data may include, for example, instructions for any application or method used to operate on the electronic device 300, and data related to the application. The memory 302 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk.

[0119] The I / O interface 303 provides an interface between the processor 301 and other interface modules, and the above-mentioned other interface modules can be keyboards, mice, buttons, etc. These buttons can be virtual buttons or physical buttons. The communication component 304 is used for wired or wireless communication between the electronic device 300 and other devices. Wireless communication, such as Wi-Fi, Bluetooth, Near Field Communication (NFC), 2G, 3G or 4G, or a combination of one or more of them, so the corresponding communication component 104 can include: Wi-Fi components, Bluetooth components, NFC components.

[0120] The electronic device 300 can be implemented by one or more application specific integrated circuits (ASIC), digital signal processors (DSP), digital signal processing devices (DSPD), programmable logic devices (PLD), field programmable gate arrays (FPGA), controllers, microcontrollers, microprocessors or other electronic components, and is used to execute the CCD size alignment inspection method for cutting and stacking equipment given in the above embodiment.

[0121] The communication bus 305 may include a path to transmit information between the above components. The communication bus 305 may be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus, etc. The communication bus 305 may be divided into an address bus, a data bus, a control bus, etc.

[0122] The electronic device 300 may include, but is not limited to, mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc., and may also be servers, etc.

[0123] The present application also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the above-mentioned CCD size alignment and inspection method for cutting and stacking equipment are implemented.

[0124] The computer-readable storage medium may include: a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and other media that can store program codes.

[0125] The terms "comprises," "comprising," or any other variations thereof are intended to cover non-exclusive inclusion such that a process, method, article, or apparatus that includes a list of elements includes not only those elements but also other elements not expressly listed, or also includes elements inherent to such process, method, article, or apparatus.

[0126] The above description is only a preferred embodiment of the present application and an explanation of the technical principles used. Those skilled in the art should understand that the scope of application involved in the present application is not limited to the technical solution formed by a specific combination of the above technical features, but should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the aforementioned application concept. For example, the above features are replaced with (but not limited to) technical features with similar functions applied in the present application.

Claims

1. A CCD size calibration and inspection method for cutting and stacking equipment, characterized in that: include: Obtain a calibration plate image containing a checkerboard area captured by a target CCD camera; Determine the coordinates of the corner points of the checkerboard area in the calibration plate image based on a preset function; Performing distortion correction on the calibration plate image based on the corner point coordinates to generate a corrected calibration plate image; Performing chessboard area division on the chessboard area in the calibration plate image to generate a chessboard area division result; Extracting pixels from the chessboard area division result to determine the identification pixels of the calibration plate image; A comparison reference value is obtained, and a calibration point inspection result is generated based on the comparison reference value and the standard pixel point.

2. The method according to claim 1, characterized in that The determining the coordinates of the corner points of the checkerboard area in the calibration plate image based on a preset function comprises: Obtaining a region corner point identifier, and determining a region corner point of the checkerboard region based on the preset function and the region corner point identifier; Based on the preset function, corner point sub-pixel extraction is performed on the corner points of the area to obtain the coordinates of the corner points of the chessboard area.

3. The method according to claim 2, characterized in that The step of performing distortion correction on the calibration plate image based on the corner point coordinates to generate a corrected calibration plate image comprises: Acquire the image coordinate system of the corner point coordinates and the camera position information of the target CCD camera; Constructing a standard physical coordinate system based on the camera position information; Determine a coordinate correspondence relationship based on the image coordinate system and the standard physical coordinate system; Calculating the distortion coefficient of the target CCD camera based on the coordinate correspondence and the corner point coordinates; The calibration plate image is subjected to distortion correction based on the distortion coefficient to generate a corrected calibration plate image.

4. The method according to claim 1, characterized in that: The performing chessboard area division on the chessboard area in the calibration plate image to generate a chessboard area division result comprises: Performing feature recognition on the calibration plate image based on a preset neural network to generate a recognition result; The recognition result is selected through a region candidate network to generate a region recognition result; Get the chessboard area information; The checkerboard area division is performed on the calibration layout based on the checkerboard area information and the area recognition result to generate a checkerboard area division result.

5. The method according to claim 1, characterized in that The step of extracting pixels from the chessboard area division result to determine the identification pixels of the calibration plate image comprises: Get pixel extraction target information; Determine a target pixel extraction point based on the pixel extraction target information and the chessboard area division result; Pixel points are extracted from the chessboard area division result based on the target pixel extraction points to obtain the identification pixel points of the correction calibration plate image.

6. The method according to claim 1, characterized in that The generating of the alignment inspection result based on the comparison reference value and the standard pixel point comprises: Obtaining a calculation rule for the comparison benchmark value; Calculate the pixel spacing of the standard pixel points based on the calculation rule to generate a spacing calculation result; Calculate the offset difference based on the spacing calculation result and the comparison reference value; Get the anomaly threshold; A calibration inspection result is generated based on the offset difference and the abnormality threshold.

7. The method according to claim 6, characterized in that Generating the alignment inspection result based on the offset difference and the abnormal threshold comprises: Calculate the offset average value based on the offset difference; Determine whether the abnormal threshold is greater than or equal to the deviation average value; If the abnormal threshold is greater than or equal to the deviation average value, the alignment inspection result is classified as a qualified state; If the abnormal threshold is less than the deviation average value, the alignment inspection result is classified as unqualified.

8. A CCD size calibration inspection system for cutting and stacking equipment, characterized in that: include: A calibration image acquisition module is used to acquire a calibration plate image containing a checkerboard area captured by a target CCD camera; A corner point coordinate determination module, used to determine the corner point coordinates of the checkerboard area in the calibration plate image based on a preset function; A correction calibration plate image generation module, used for performing distortion correction on the calibration plate image based on the corner point coordinates to generate a correction calibration plate image; A chessboard result generation module, used to perform chessboard area division on the chessboard area in the calibration plate image and generate a chessboard area division result; A marking pixel determination module is used to extract pixel points from the chessboard area division result to determine the marking pixel points of the calibration plate image; The spot inspection result generating module is used to obtain a comparison reference value, and generate a calibration spot inspection result based on the comparison reference value and the standard pixel point.

9. An electronic device, characterized in that: comprising a processor coupled to a memory; The processor is configured to execute a computer program stored in the memory, so that the electronic device executes the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The method comprises a computer program or an instruction, which, when executed on a computer, causes the computer to execute the method according to any one of claims 1 to 7.

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