A metal stamping detection method and system based on machine vision

Abstract

The present application provides a method and system for detecting metal stamping based on machine vision. The real-time image of the target part being stamped is collected by a camera device; the real-time image is enhanced to generate an enhanced image corresponding to the real-time image, and the image features in the enhanced image are extracted; the standard features corresponding to the target part are obtained based on the device identification of the target part; the image features are compared with the standard features to determine the target area to be adjusted; and the target area is stamped. By performing image enhancement and feature extraction on the acquired real-time image, and performing feature comparison to determine the target area to be adjusted, the accuracy of visual detection of metal stamping effects is improved; the entire processing process is automated and intelligent, reducing the need for manual intervention and improving production efficiency; the stamping parameters can be automatically adjusted according to real-time data, adaptive control is achieved, and the flexibility and adaptability of the system are improved.

Description

Technical Field

[0001] The present application relates to the field of computer technology, and in particular to a metal stamping detection method and system based on machine vision. Background Art

[0002] Metal stamping is a process that uses a punch press and a die to deform or break stainless steel, iron, aluminum, copper and other special materials to achieve a specific shape and size. This process is sometimes also called sheet metal forming, but the two are slightly different. Sheet metal forming mainly refers to the forming method that uses sheet metal, thin-walled tubes, thin profiles, etc. as raw materials for plastic processing, while metal stamping focuses more on using a punch press and a die to achieve this process.

[0003] However, in the existing metal stamping process, the stamping effect is detected by manual detection, resulting in low detection efficiency and accuracy in the metal stamping process. Summary of the invention

[0004] The embodiments of the present application provide a method and system for metal stamping detection based on machine vision, which can at least to a certain extent solve the problem of low efficiency and accuracy of metal stamping detection.

[0005] Other features and advantages of the present application will become apparent from the following detailed description, or may be learned in part by the practice of the present application.

[0006] According to one aspect of the present application, a metal stamping detection method based on machine vision is provided, comprising: during the stamping process, collecting a real-time image of a target part being stamped by a camera device; enhancing the real-time image to generate an enhanced image corresponding to the real-time image, and extracting image features in the enhanced image; based on the equipment identification of the target part, obtaining the standard features corresponding to the target part; comparing the image features with the standard features, and determining a target area to be adjusted according to the comparison results; and stamping the target area.

[0007] In the present application, based on the aforementioned scheme, during the stamping process, a real-time image of the target part being stamped is collected by a camera device, including: during the stamping process, angle images of the target part being stamped are collected by cameras installed at different angles; the angle images are stitched to generate the real-time image.

[0008] In the present application, based on the aforementioned scheme, the real-time image is enhanced to generate an enhanced image corresponding to the real-time image, and image features in the enhanced image are extracted, including: based on the pixel value of each pixel in the real-time image, determining enhancement parameters for image enhancement; based on the enhancement parameters, the real-time image is enhanced to generate the enhanced image; based on the pixel value of each pixel in the enhanced image, determining feature parameters for feature extraction; based on the feature parameters, extracting image features in the enhanced image.

[0009] In the present application, based on the aforementioned scheme, the method of obtaining the standard features corresponding to the target part based on the device identification of the target part includes: obtaining the device identification of the target part; and matching from a database based on the device identification to determine the standard features corresponding to the target part.

[0010] In the present application, based on the aforementioned scheme, the image features are compared with the standard features, and the target area to be adjusted is determined according to the comparison results, including: based on the image features and the standard features, feature partitioning is performed to generate at least two feature areas; the difference parameters between the image features and the standard features corresponding to each feature area are calculated; and the target area to be adjusted is determined according to the difference parameters.

[0011] In the present application, based on the above-mentioned solution, the image feature includes at least one of the following: color, texture, shape, edge, corner point and key point.

[0012] In the present application, based on the aforementioned solution, the method further includes: scoring the stamping degree of the target part based on the comparison result between the image feature and the standard feature.

[0013] According to one aspect of the present application, a metal stamping detection system based on machine vision is provided, comprising:

[0014] An acquisition unit, used to collect a real-time image of the punched target part through a camera device during the punching process;

[0015] An enhancement unit, used to perform enhancement processing on the real-time image, generate an enhanced image corresponding to the real-time image, and extract image features from the enhanced image;

[0016] A feature unit, used for acquiring a standard feature corresponding to the target part based on a device identification of the target part;

[0017] A comparison unit, used for comparing the image feature with the standard feature, and determining a target area to be adjusted according to the comparison result;

[0018] A processing unit is used to perform a stamping process on the target area.

[0019] In the present application, based on the aforementioned solution, the acquisition unit is specifically used to collect angle images of the punched target part through cameras installed at different angles during the stamping process; and to splice the angle images to generate the real-time image.

[0020] In the present application, based on the aforementioned scheme, the enhancement unit is specifically used to determine the enhancement parameters for image enhancement based on the pixel value of each pixel in the real-time image; enhance the real-time image based on the enhancement parameters to generate the enhanced image; determine the feature parameters for feature extraction based on the pixel value of each pixel in the enhanced image; and extract image features in the enhanced image based on the feature parameters.

[0021] In the technical solution of the present application, during the stamping process, a real-time image of the target part being stamped is collected by a camera device; the real-time image is enhanced to generate an enhanced image corresponding to the real-time image, and image features in the enhanced image are extracted; based on the device identification of the target part, the standard features corresponding to the target part are obtained; the image features are compared with the standard features, and the target area to be adjusted is determined according to the comparison results; and the target area is stamped. The technical solution of the present application improves the accuracy of visual detection of metal stamping effects by performing image enhancement and feature extraction on the acquired real-time image, and performing feature comparison to determine the target area to be adjusted; the entire processing process is automated and intelligent, reducing the need for manual intervention and improving production efficiency; the stamping parameters can be automatically adjusted according to real-time data, adaptive control is achieved, and the flexibility and adaptability of the system are improved.

[0022] It should be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] The drawings herein are incorporated into the specification and constitute a part of the specification, illustrate embodiments consistent with the present application, and together with the specification are used to explain the principles of the present application. Obviously, the drawings described below are only some embodiments of the present application, and for ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0024] Figure 1 The flowchart of a metal stamping detection method based on machine vision in one embodiment of the present application is schematically shown.

[0025] Figure 2 The flowchart of extracting image features in one embodiment of the present application is schematically shown.

[0026] Figure 3 A schematic diagram of a metal stamping detection system based on machine vision in one embodiment of the present application is schematically shown.

[0027] Figure 4 A schematic diagram of the structure of a computer system suitable for implementing an electronic device of an embodiment of the present application is shown. DETAILED DESCRIPTION

[0028] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be implemented in a variety of forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that this application will be more comprehensive and complete and fully convey the concept of the example embodiments to those skilled in the art.

[0029] In addition, described feature, structure or characteristic can be combined in one or more embodiments in any suitable manner. In the following description, many specific details are provided to provide a full understanding of the embodiments of the present application. However, those skilled in the art will appreciate that the technical scheme of the present application can be put into practice without one or more of the specific details, or other methods, components, devices, steps, etc. can be adopted. In other cases, known methods, devices, realizations or operations are not shown or described in detail to avoid blurring the various aspects of the application.

[0030] The block diagrams shown in the accompanying drawings are merely functional entities and do not necessarily correspond to physically independent entities. That is, these functional entities may be implemented in software form, or in one or more hardware modules or integrated circuits, or in different networks and / or processor devices and / or microcontroller devices.

[0031] The flowcharts shown in the accompanying drawings are only exemplary and do not necessarily include all the contents and operations / steps, nor must they be executed in the order described. For example, some operations / steps can be decomposed, and some operations / steps can be combined or partially combined, so the actual execution order may change according to actual conditions.

[0032] The implementation details of the technical solution of this application are described in detail below:

[0033] Figure 1 The flowchart of the metal stamping detection method based on machine vision according to one embodiment of the present application is shown. Figure 1 As shown, the metal stamping detection method based on machine vision includes at least steps S110 to S150, which are described in detail as follows:

[0034] In step S110, during the stamping process, a real-time image of the target part being stamped is collected by a camera device.

[0035] In one embodiment of the present application, during the stamping process, the camera device is started to start real-time shooting of the target part being stamped. The camera device continuously shoots images of the target part during the stamping process and transmits them to a computer or other processing device. As needed, the shooting parameters of the camera device, such as exposure time, white balance, etc., can be set to obtain a clearer image.

[0036] In one embodiment of the present application, during the stamping process, a real-time image of a stamped target part is collected by a camera device, including:

[0037] During the stamping process, the camera devices installed at different angles are used to collect angle images of the target part being stamped;

[0038] The angle images are spliced ​​to generate the real-time image.

[0039] In one embodiment of the present application, in this embodiment, camera devices with different angles are installed around the target part to capture angle images of the target part at multiple angles, thereby improving the comprehensiveness of image acquisition.

[0040] After obtaining the angle images of the target part at different angles, the angle images are spliced ​​to generate a real-time image. In this way, the real-time image can include information of the target part at each angle.

[0041] In the above process, the camera device can collect the image of the target part in real time, monitor the status of the stamping process in real time, and promptly discover and deal with potential problems. By adjusting the stamping parameters or intervening in real time, it helps to reduce the scrap rate and improve product quality.

[0042] In step S120, the real-time image is enhanced to generate an enhanced image corresponding to the real-time image, and image features in the enhanced image are extracted.

[0043] like Figure 2 As shown, in one embodiment of the present application, the real-time image is enhanced to generate an enhanced image corresponding to the real-time image, and image features in the enhanced image are extracted, including:

[0044] S210, determining enhancement parameters for image enhancement based on the pixel value of each pixel in the real-time image;

[0045] S220, performing enhancement processing on the real-time image based on the enhancement parameters to generate the enhanced image;

[0046] S230, determining feature parameters for feature extraction based on the pixel values ​​of pixels in the enhanced image;

[0047] S240: Extract image features in the enhanced image based on the feature parameters.

[0048] In one embodiment of the present application, by obtaining the pixel value of each pixel in the real-time image , to determine the enhancement parameters based on pixel values :

[0049]

[0050] Among them, i and j represent the location information of the pixel points, and n and m represent the number of pixels in the horizontal and vertical directions of the real-time image, respectively. Indicates the preset pixel factor, Represents the enhancement factor determined based on historical data.

[0051] Through the above process, enhancement parameters are generated based on the pixel values ​​of the pixels in the real-time image, so as to measure and represent the pixel level in the real-time image through the enhancement parameters. Then, the real-time image is enhanced based on the enhancement parameters to generate an enhanced image. Specifically, the enhancement processing of the real-time image includes determining the pixel value corresponding to each pixel in the real-time image based on the enhancement parameters. :

[0052]

[0053] After the pixel values ​​are calculated, an enhanced image is generated based on the pixel values. The above process enhances the pixel points in the real-time image based on the enhancement parameters, thereby improving the pixel contrast in the real-time image and highlighting the image features in the real-time image. , determine the feature parameters used for feature extraction for:

[0054]

[0055] in, Represents a preset feature factor. After the feature parameter is calculated, the image feature in the enhanced image is extracted based on the feature parameter. For example, the feature of the pixel value in the enhanced image is extracted as the image feature. In this way, the recognition of the image feature is improved, thereby enhancing the accuracy of feature recognition.

[0056] In this embodiment, the features include: color, texture, shape, edge, corner point, key point, etc.

[0057] The above process can improve the visual effect of the image by enhancing the real-time image, highlight the key features of the target part, and provide higher quality input for subsequent feature extraction and comparison. Extracting image features from the enhanced image can accurately capture key information such as the shape, size, and texture of the target part, providing a reliable basis for comparison and evaluation.

[0058] In step S130, based on the device identification of the target part, the standard features corresponding to the target part are acquired.

[0059] In one embodiment of the present application, first, the device identification of the target part is identified from the real-time image captured by the camera device. This can usually be achieved through image processing technology (such as OCR optical character recognition, template matching, etc.). The device identification may be a unique barcode, QR code, serial number or other identifiable mark on the target part. Once the device identification is successfully identified, the next step is to query the information corresponding to the device identification in a pre-established database. This database usually contains various target parts and their related detailed information, including their standard features. In the database, the standard features related to the target part are retrieved based on the device identification.

[0060] In one embodiment of the present application, based on the device identification of the target part, obtaining the standard feature corresponding to the target part includes:

[0061] Obtaining a device identification of the target component;

[0062] Based on the equipment identification, a match is performed from a database to determine the standard features corresponding to the target part.

[0063] In one embodiment of the present application, by scanning the device identification on the target part, matching is performed from a database based on the device identification to determine the standard features corresponding to the target part.

[0064] Specifically, in this embodiment, a database is preset, in which the device identification of the target part and its corresponding standard features are stored in association, and the corresponding standard features can be queried through the device identification. , the multiple identifiers stored in the database are: , compare the target device identification with the identification in the database one by one, and calculate the similarity between the two as :

[0065]

[0066] in, , Respectively represent the string corresponding to the device identification, g represents the character order in the string, and k represents the number of characters in the string. The above process matches the similarity between the device identification and the database identification, determines the target identification corresponding to the device identification with the highest similarity, and obtains the features corresponding to the target identification as the standard features.

[0067] In this embodiment, the standard features include standard images, key dimensions, shape parameters, texture features, etc. of the target part at different stamping degrees.

[0068] It should be noted that the standard features in this embodiment include the set features and target features of the hardware, that is, the target features that the hardware should have after stamping is completed.

[0069] The above process, based on the device identification of the target part, can accurately obtain the corresponding standard features, avoiding the tedious process of manually searching or setting standard features. Standard features, as a reference benchmark, help to quantitatively evaluate the difference between the target part and the ideal state, and provide a basis for adjustment.

[0070] In step S140, the image features are compared with the standard features, and the target area to be adjusted is determined according to the comparison result.

[0071] In one embodiment of the present application, the extracted image features are compared with the standard features. The comparison method may include calculating the similarity, distance or other metric between the features. Various algorithms and techniques can be used for comparison, such as Euclidean distance, cosine similarity, feature point matching, etc.

[0072] Analyze the comparison results to determine the differences between the target part and the standard part. These differences may be reflected in shape deformation, dimensional deviation, texture change, etc. Based on the comparison results, a difference map or difference matrix can be generated to visualize the differences between the target part and the standard part. Based on the comparison results and analysis, determine the target areas that need to be adjusted. These areas are usually parts that have significant differences from the standard features. Thresholding methods, region growing methods, contour detection, etc. can be used to determine the target areas to be adjusted.

[0073] In one embodiment of the present application, comparing the image feature with the standard feature, and determining the target area to be adjusted according to the comparison result, includes:

[0074] Based on the image features and the standard features, feature partitioning is performed to generate at least two feature areas;

[0075] Calculate the difference parameters between the image features corresponding to each feature area and the standard features;

[0076] A target area to be adjusted is determined according to the difference parameter.

[0077] In one embodiment of the present application, since the image plate is relatively large, the image features are partitioned to generate at least two feature regions. Therefore, the feature partitioning is performed, for example, the image is averagely cut to generate two feature regions.

[0078] In the same feature area, the difference parameters between the image features and the standard features corresponding to each feature area are calculated to measure the difference between the real-time image and the standard image, so as to determine the target area to be adjusted according to the difference parameters, that is, the area with the difference parameter greater than or equal to the set threshold is taken as the target area.

[0079] The above process can accurately identify the difference area between the target part and the standard part through the precise comparison between the image features and the standard features. Determining the target area to be adjusted helps to achieve accurate stamping adjustment and improve stamping accuracy.

[0080] In step S150, a stamping process is performed on the target area.

[0081] In one embodiment of the present application, after the target area is determined, the determined target area to be adjusted is optimized to reduce or eliminate the difference with the standard features. This may include operations such as shape correction, size adjustment, texture repair, etc. The optimization method can be selected and designed according to the specific application scenario and requirements.

[0082] In one embodiment of the present application, the method further includes: scoring the stamping degree of the target part based on the comparison result between the image feature and the standard feature.

[0083] In this embodiment, the stamping degree of the target part is scored according to the comparison result. The scoring rules can be formulated according to actual needs. For example, the stamping degree can be divided into several levels and a score range is assigned to each level. The scoring results are output to a display, report or other form of document for subsequent analysis or decision-making.

[0084] In the technical solution of the present application, during the stamping process, a real-time image of the target part being stamped is collected by a camera device; the real-time image is enhanced to generate an enhanced image corresponding to the real-time image, and image features in the enhanced image are extracted; based on the device identification of the target part, the standard features corresponding to the target part are obtained; the image features are compared with the standard features, and the target area to be adjusted is determined according to the comparison results; and the target area is stamped. The technical solution of the present application improves the efficiency and accuracy of visual detection of metal stamping effects by performing image enhancement and feature extraction on the acquired real-time image, and performing feature comparison to determine the target area to be adjusted. The system can automatically adjust stamping parameters according to real-time data, realize adaptive control, and improve the flexibility and adaptability of the system.

[0085] The following describes an embodiment of the device of the present application, which can be used to execute the metal stamping detection method based on machine vision in the above embodiment of the present application. It can be understood that the device can be a computer program (including program code) running in a computer device, for example, the device is an application software; the device can be used to execute the corresponding steps in the method provided in the embodiment of the present application. For details not disclosed in the embodiment of the device of the present application, please refer to the embodiment of the metal stamping detection method based on machine vision in the above embodiment of the present application.

[0086] Figure 3 A block diagram of a metal stamping inspection system based on machine vision according to an embodiment of the present application is shown.

[0087] Reference Figure 3 As shown, a metal stamping detection system based on machine vision according to an embodiment of the present application includes:

[0088] The acquisition unit 310 is used to collect a real-time image of the punched target part through a camera device during the punching process;

[0089] The enhancement unit 320 is used to perform enhancement processing on the real-time image, generate an enhanced image corresponding to the real-time image, and extract image features from the enhanced image;

[0090] A feature unit 330, configured to obtain a standard feature corresponding to the target part based on the device identification of the target part;

[0091] A comparison unit 340, configured to compare the image feature with the standard feature and determine a target area to be adjusted according to the comparison result;

[0092] The processing unit 350 is used to perform a stamping process on the target area.

[0093] In the present application, based on the aforementioned solution, the acquisition unit 310 is specifically used to collect angle images of the punched target part through cameras installed at different angles during the stamping process; and to stitch the angle images to generate the real-time image.

[0094] In the present application, based on the aforementioned scheme, the enhancement unit 320 is specifically used to determine the enhancement parameters for image enhancement based on the pixel value of each pixel in the real-time image; enhance the real-time image based on the enhancement parameters to generate the enhanced image; determine the feature parameters for feature extraction based on the pixel value of each pixel in the enhanced image; and extract image features in the enhanced image based on the feature parameters.

[0095] In the present application, based on the above-mentioned solution, the feature unit 330 is specifically used to obtain the device identification of the target part; based on the device identification, matching is performed from the database to determine the standard features corresponding to the target part.

[0096] In the present application, based on the aforementioned scheme, the comparison unit 340 is specifically used to perform feature partitioning based on the image features and the standard features to generate at least two feature areas; calculate the difference parameters between the image features and the standard features corresponding to each feature area; and determine the target area to be adjusted based on the difference parameters.

[0097] In the present application, based on the above-mentioned solution, the image features include at least one of the following: color, texture, shape, edge, corner point and key point.

[0098] In the present application, based on the aforementioned solution, the system further includes: a scoring unit, which is used to score the stamping degree of the target part based on the comparison result between the image feature and the standard feature.

[0099] In the technical solution of the present application, during the stamping process, a real-time image of the target part being stamped is collected by a camera device; the real-time image is enhanced to generate an enhanced image corresponding to the real-time image, and image features in the enhanced image are extracted; based on the device identification of the target part, the standard features corresponding to the target part are obtained; the image features are compared with the standard features, and the target area to be adjusted is determined according to the comparison results; and the target area is stamped. The technical solution of the present application improves the efficiency and accuracy of visual detection of metal stamping effects by performing image enhancement and feature extraction on the acquired real-time image, and performing feature comparison to determine the target area to be adjusted.

[0100] Figure 4 A schematic diagram of the structure of a computer system suitable for implementing an electronic device of an embodiment of the present application is shown.

[0101] It should be noted that the computer system 400 of the electronic device shown in the figure is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0102] The computer system 400 includes a central processing unit (CPU) 401, which can perform various appropriate actions and processes according to the program stored in the read-only memory (ROM) 402 or the program loaded from the storage part 408 to the random access memory (RAM) 403, such as executing the method described in the above embodiment. Various programs and data required for system operation are also stored in the RAM 403. The CPU 401, the ROM 402 and the RAM 403 are connected to each other through the bus 404. The input / output (I / O) interface 405 is also connected to the bus 404.

[0103] The following components are connected to the I / O interface 405: an input section 406 including a keyboard, a mouse, etc.; an output section 407 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 408 including a hard disk, etc.; and a communication section 409 including a network interface card such as a LAN (Local Area Network) card, a modem, etc. The communication section 409 performs communication processing via a network such as the Internet. A drive 410 is also connected to the I / O interface 405 as needed. A removable medium 411, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 410 as needed so that a computer program read therefrom is installed into the storage section 408 as needed.

[0104] In particular, according to an embodiment of the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present application includes a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a computer program for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through the communication part 409, and / or installed from a removable medium 411. When the computer program is executed by the central processing unit (CPU) 401, various functions defined in the system of the present application are executed.

[0105] It should be noted that the computer-readable medium shown in the embodiment of the present application may be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a flash memory, an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present application, a computer-readable storage medium may be any tangible medium containing or storing a program, which may be used by or in combination with an instruction execution system, device or device. In the present application, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, which carries a computer-readable computer program. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Computer-readable signal media may also be any computer-readable medium other than computer-readable storage media, which may send, propagate, or transmit programs for use by or in conjunction with an instruction execution system, apparatus, or device. The computer program contained on the computer-readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wired, etc., or any suitable combination of the above.

[0106] The flowchart and block diagram in the accompanying drawings illustrate the possible architecture, functions and operations of the system, method and computer program product according to various embodiments of the present application. Wherein, each box in the flowchart or block diagram can represent a module, a program segment, or a part of the code, and the above-mentioned module, program segment, or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flowchart, and the combination of boxes in the block diagram or flowchart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0107] The units involved in the embodiments described in this application may be implemented by software or hardware, and the units described may also be set in a processor. The names of these units do not, in some cases, constitute limitations on the units themselves.

[0108] According to one aspect of the present application, a computer program product or a computer program is provided, the computer program product or the computer program comprising computer instructions, the computer instructions being stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device executes the methods provided in the above-mentioned various optional implementations.

[0109] As another aspect, the present application also provides a computer-readable medium, which may be included in the electronic device described in the above embodiment; or may exist independently without being assembled into the electronic device. The above computer-readable medium carries one or more programs, and when the above one or more programs are executed by an electronic device, the electronic device implements the method described in the above embodiment.

[0110] It should be noted that, although several modules or units of the equipment for action execution are mentioned in the above detailed description, this division is not mandatory. In fact, according to the embodiments of the present application, the features and functions of two or more modules or units described above can be embodied in one module or unit. On the contrary, the features and functions of one module or unit described above can be further divided into being embodied by multiple modules or units.

[0111] Through the description of the above implementation methods, it is easy for those skilled in the art to understand that the example implementation methods described here can be implemented by software, or by combining software with necessary hardware. Therefore, the technical solution according to the implementation method of the present application can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on a network, including several instructions to enable a computing device (which can be a personal computer, a server, a touch terminal, or a network device, etc.) to execute the method according to the implementation method of the present application.

[0112] Those skilled in the art will readily appreciate other embodiments of the present application after considering the specification and practicing the embodiments disclosed herein. The present application is intended to cover any variations, uses or adaptations of the present application, which follow the general principles of the present application and include common knowledge or customary technical means in the art that are not disclosed in the present application.

[0113] It should be understood that the present application is not limited to the precise structures that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present application is limited only by the appended claims.

Claims

1. A metal stamping detection method based on machine vision, characterized in that: include: During the stamping process, a real-time image of the target part being stamped is collected by a camera device; Performing enhancement processing on the real-time image to generate an enhanced image corresponding to the real-time image, and extracting image features in the enhanced image; Based on the equipment identification of the target part, the standard features corresponding to the target part are obtained, wherein the standard features include the standard image, key dimensions, shape parameters, and texture features of the target part at different stamping degrees; Comparing the image features with the standard features, and determining the target area to be adjusted according to the comparison result; Performing a stamping process on the target area; The step of performing enhancement processing on the real-time image to generate an enhanced image corresponding to the real-time image and extracting image features from the enhanced image includes: Based on the pixel value of each pixel in the real-time image , determine the enhancement parameters used for image enhancement for: in, represents the enhancement factor determined based on historical data, i, j represent the location information of the pixel points, n, m represent the number of pixels in the horizontal and vertical directions of the real-time image, respectively. Indicates the preset pixel factor; The real-time image is enhanced based on the enhancement parameters to determine the pixel value corresponding to each pixel in the real-time image. for: After the pixel values ​​are calculated, the enhanced image is generated based on the pixel values; Based on the pixel value of each pixel in the enhanced image, a feature parameter for feature extraction is determined. for: in, represents a preset characteristic factor; Based on the feature parameters, image features in the enhanced image are extracted.

2. The method according to claim 1, characterized in that During the stamping process, the real-time image of the target part being stamped is collected by the camera device, including: During the stamping process, the camera devices installed at different angles are used to collect angle images of the target part being stamped; The angle images are spliced ​​to generate the real-time image.

3. The method according to claim 1, characterized in that: Based on the device identification of the target part, obtaining the standard features corresponding to the target part includes: Obtaining a device identification of the target component; Based on the equipment identification, a match is performed from a database to determine the standard features corresponding to the target part.

4. The method according to claim 1, characterized in that: Comparing the image feature with the standard feature and determining the target area to be adjusted according to the comparison result includes: Based on the image features and the standard features, feature partitioning is performed to generate at least two feature areas; Calculate the difference parameters between the image features corresponding to each feature area and the standard features; A target area to be adjusted is determined according to the difference parameter.

5. The method according to claim 1, characterized in that The image features include at least one of the following: color, texture, shape, edge, corner point and key point.

6. The method according to claim 1, characterized in that The method further comprises: Based on the comparison result between the image feature and the standard feature, the stamping degree of the target part is scored.

7. A metal stamping detection system based on machine vision, characterized in that: include: An acquisition unit, used to collect a real-time image of the punched target part through a camera device during the punching process; An enhancement unit, used to perform enhancement processing on the real-time image, generate an enhanced image corresponding to the real-time image, and extract image features from the enhanced image; A feature unit, used to obtain standard features corresponding to the target part based on the equipment identification of the target part, wherein the standard features include standard images, key dimensions, shape parameters, and texture features of the target part at different stamping degrees; A comparison unit, used for comparing the image feature with the standard feature, and determining a target area to be adjusted according to the comparison result; A processing unit, used for performing a stamping process on the target area; The step of performing enhancement processing on the real-time image to generate an enhanced image corresponding to the real-time image and extracting image features from the enhanced image includes: Based on the pixel value of each pixel in the real-time image , determine the enhancement parameters used for image enhancement for: in, represents the enhancement factor determined based on historical data, i, j represent the location information of the pixel points, n, m represent the number of pixels in the horizontal and vertical directions of the real-time image, respectively. Indicates the preset pixel factor; The real-time image is enhanced based on the enhancement parameters to determine the pixel value corresponding to each pixel in the real-time image. for: After the pixel values ​​are calculated, the enhanced image is generated based on the pixel values; Based on the pixel value of each pixel in the enhanced image, a feature parameter for feature extraction is determined. for: in, represents a preset characteristic factor; Based on the feature parameters, image features in the enhanced image are extracted.

8. The system according to claim 7, characterized in that The acquisition unit is specifically used for collecting angle images of the punched target part through cameras installed at different angles during the punching process; and splicing the angle images to generate the real-time image.

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