CN117132586A - Defect detection method and device for card support bracket, computer equipment and storage medium - Google Patents

Defect detection method and device for card support bracket, computer equipment and storage medium Download PDF

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Publication number
CN117132586A
CN117132586A CN202311356994.6A CN202311356994A CN117132586A CN 117132586 A CN117132586 A CN 117132586A CN 202311356994 A CN202311356994 A CN 202311356994A CN 117132586 A CN117132586 A CN 117132586A
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China
Prior art keywords
card
image
bracket
card support
detection area
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CN202311356994.6A
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Chinese (zh)
Inventor
石璕
鞠游
朱豪
杨勋涛
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Shenzhen Zhiji Vision Technology Co ltd
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Shenzhen Zhiji Vision Technology Co ltd
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Priority to CN202311356994.6A priority Critical patent/CN117132586A/en
Publication of CN117132586A publication Critical patent/CN117132586A/en
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/0002—Inspection of images, e.g. flaw detection
    • G06T7/0004—Industrial image inspection
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/10—Segmentation; Edge detection
    • G06T7/11—Region-based segmentation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/10—Segmentation; Edge detection
    • G06T7/136—Segmentation; Edge detection involving thresholding
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/70—Determining position or orientation of objects or cameras
    • G06T7/73—Determining position or orientation of objects or cameras using feature-based methods
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30108—Industrial image inspection
    • G06T2207/30164—Workpiece; Machine component
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
    • Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
    • Y02P90/30—Computing systems specially adapted for manufacturing

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  • Engineering & Computer Science (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Quality & Reliability (AREA)
  • Image Processing (AREA)

Abstract

The application relates to vision measurement technology, and discloses a defect detection method of a card support bracket, which comprises the following steps: acquiring a bracket image of a card bracket, wherein the bracket image at least comprises a card bracket image; performing edge detection on the card support image to identify a first detection area and a second detection area, wherein the first detection area comprises a card support boundary, and the second detection area is a card slot area; converting the card support image into a gray image; and respectively detecting deformation defects of the gray images in the first detection area and the second detection area based on a preset card support layout. The application also discloses a defect detection device, a computer device and a computer readable storage medium. The application aims to improve the accuracy and efficiency of defect detection of the card support bracket.

Description

Defect detection method and device for card support bracket, computer equipment and storage medium
Technical Field
The present application relates to the field of vision measurement technologies, and in particular, to a defect detection method, a defect detection device, a computer device, and a computer readable storage medium for a card support.
Background
At present, for mobile communication and storage expansion, a smart device (such as a smart phone and a smart watch) is generally configured with a mobile communication module and a memory expansion module, and a corresponding card support bracket is configured, wherein a card slot for accommodating a SIM card or a memory card is arranged on the card support bracket, and the SIM card or the memory card can be conveniently inserted into (or taken out from) the smart device by using the card support bracket.
Therefore, the card support is one of the components of the smart device, and in order to ensure the production quality, the card support needs to be subjected to defect detection, such as deformation detection, scratch detection, and the like, wherein the deformation detection is particularly important, because once the card support is deformed, a serious defect that the card slot cannot accommodate the SIM card (or the memory card) or the card support cannot be inserted into the smart device occurs.
At present, the defect detection of the card support bracket is generally performed manually, and the manual detection generally has certain subjectivity, so that the error is large, the detection result is often uncertain, the judgment of the detection result is completely dependent on the working experience and subjective consciousness of workers, and the detection result of the product is unstable; in addition, the card support bracket is generally small in size, accurate detection of key defects is difficult to complete only by naked eyes, and particularly the specifications of the current SIM card are smaller and smaller, and the corresponding card support bracket is smaller and smaller, so that the difficulty of defect detection is increased.
The foregoing is provided merely for the purpose of facilitating understanding of the technical solutions of the present application and is not intended to represent an admission that the foregoing is prior art.
Disclosure of Invention
The application mainly aims to provide a defect detection method, a defect detection device, computer equipment and a computer readable storage medium for a card support bracket, aiming at improving the accuracy and efficiency of defect detection for the card support bracket.
In order to achieve the above object, the present application provides a defect detection method of a card support bracket, where the card support bracket includes a card support and a stop portion disposed on a side surface of the card support; the card holder is provided with a card slot, and the card slot is used for placing a SIM card or a memory card; the defect detection method of the card support bracket comprises the following steps:
acquiring a bracket image of a card bracket, wherein the bracket image at least comprises a card bracket image;
performing edge detection on the card support image to identify a first detection area and a second detection area, wherein the first detection area comprises a card support boundary, and the second detection area is a card slot area;
converting the card support image into a gray image;
and respectively detecting deformation defects of the gray images in the first detection area and the second detection area based on a preset card support layout.
Optionally, the stent image further comprises a stop image; after the step of obtaining the bracket image of the card bracket, the method further comprises the following steps:
identifying feature point locations in the stop image;
determining a third detection area corresponding to the stop part image according to the characteristic point position;
the defect detection method of the card support bracket further comprises the following steps:
and respectively detecting the crush injury defects of the images in the third detection area and the fourth detection area, wherein the fourth detection area is an area in the card support boundary.
Optionally, the feature point is a position of a pinhole of the stop portion, and the third detection area is a ring-shaped area.
Optionally, after the step of performing the crush injury defect detection on the images in the third detection area and the fourth detection area, the method further includes:
converting the stent image into a binarized image;
and respectively carrying out scratch defect detection and/or plaque defect detection on the binarized images in the third detection area and the fourth detection area.
Optionally, the defect detection method of the card support bracket further includes:
when detecting that the card support bracket has defects, marking corresponding defects in the bracket image by using preset colors.
Optionally, the defect detection method of the card support bracket further includes:
when the bracket image is acquired, controlling a mechanical arm clamping the camera to adjust the shooting angle of the camera when the camera is controlled to acquire the card bracket image, so that the camera can continuously acquire the stop part image;
or when the camera is controlled to acquire the image of the stop part, controlling the mechanical arm clamping the camera to adjust the shooting angle of the camera so that the camera can continuously acquire the card support image.
Optionally, the defect detection method of the card support bracket further includes:
when the bracket image is acquired, when the camera is controlled to acquire the card bracket image, the mechanical arm supporting the card bracket is controlled to align the stop part of the card bracket to the lens of the camera so as to enable the front of the camera to acquire the stop part image;
or when the camera is controlled to acquire the image of the stop part, the mechanical arm supporting the card support bracket is controlled to align the card support of the card support bracket to the lens of the camera, so that the front of the camera acquires the image of the card support.
In order to achieve the above object, the present application also provides a defect detecting apparatus, comprising:
the image acquisition module is used for acquiring a bracket image of the card bracket, wherein the bracket image at least comprises a card bracket image; the card support comprises a card support and a stop part arranged on the side face of the card support, wherein a card slot is arranged in the card support and is used for placing a SIM card or a memory card;
the area identification module is used for carrying out edge detection on the card support image so as to identify a first detection area and a second detection area, wherein the first detection area comprises a card support boundary, and the second detection area is a card slot area;
the image conversion module is used for converting the card support image into a gray image;
and the defect detection module is used for respectively carrying out deformation defect detection on the gray level images in the first detection area and the second detection area based on a preset card support layout.
To achieve the above object, the present application also provides a computer apparatus comprising: the device comprises a memory, a processor and a computer program stored in the memory and capable of running on the processor, wherein the computer program is executed by the processor to realize the steps of the defect detection method of the card support bracket.
To achieve the above object, the present application also provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements the steps of the defect detection method of a card holder bracket as described above.
The defect detection method, the defect detection device, the computer equipment and the computer readable storage medium of the card support bracket provided by the application are based on computer vision and image processing technology, automatically identify the card support boundary and the card slot in the card support bracket, automatically complete corresponding deformation defect detection, overcome the problems of high subjectivity and error in the traditional manual inspection, improve the accuracy and efficiency of deformation defect detection of the card support bracket, and save the cost of manual detection.
Drawings
FIG. 1 is a schematic diagram showing steps of a defect detection method of a card holder according to an embodiment of the application;
FIG. 2 is a schematic diagram of a defect detecting apparatus according to an embodiment of the application;
fig. 3 is a schematic block diagram illustrating an internal structure of a computer device according to an embodiment of the present application.
The achievement of the objects, functional features and advantages of the present application will be further described with reference to the accompanying drawings, in conjunction with the embodiments.
Detailed Description
Embodiments of the present application are described in detail below, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to like or similar elements or elements having like or similar functions throughout. The embodiments described below are exemplary and intended to illustrate the present application and should not be construed as limiting the application, and all other embodiments, based on the embodiments of the present application, which may be obtained by persons of ordinary skill in the art without inventive effort, are within the scope of the present application.
Furthermore, the description of "first," "second," etc. in this disclosure is for descriptive purposes only (e.g., to distinguish between identical or similar elements) and is not to be construed as indicating or implying a relative importance or an implicit indication of the number of features indicated. Thus, a feature defining "a first" or "a second" may explicitly or implicitly include at least one such feature. In addition, the technical solutions of the embodiments may be combined with each other, but it is necessary to base that the technical solutions can be realized by those skilled in the art, and when the technical solutions are contradictory or cannot be realized, the combination of the technical solutions should be considered to be absent and not within the scope of protection claimed in the present application.
In one embodiment, a defect detection method of a card support is provided, wherein the card support comprises a card support and a stop part arranged on the side surface of the card support; the card holder is provided with a card slot, and the card slot is used for placing a SIM card or a memory card; referring to fig. 1, the defect detection method of the card support bracket includes:
s10, acquiring a bracket image of a card bracket, wherein the bracket image at least comprises a card bracket image;
step S20, carrying out edge detection on the card holder image to identify a first detection area and a second detection area, wherein the first detection area comprises a card holder boundary, and the second detection area is a card slot area;
s30, converting the card support image into a gray image;
and S40, respectively detecting deformation defects of the gray level images in the first detection area and the second detection area based on a preset card support layout.
In this embodiment, the execution terminal of the embodiment may be a computer device, or may be another device or apparatus for controlling the computer device (such as a defect detection apparatus).
It should be understood that the card support bracket of the intelligent device comprises a card support and a stop part arranged on the side surface of the card support; one or more clamping grooves are formed in the card holder and used for placing the SIM card or the memory card; and the stop part arranged on the side surface of the card support is used for enabling the support interface to be closed when the card support bracket is inserted into the card support bracket interface of the intelligent equipment, namely, the stop part can be aligned with the support interface of the intelligent equipment and is fixed in a closing manner, so that the card support bracket is ensured to be firmly connected with the intelligent equipment interface, and the intelligent equipment interface is dustproof and waterproof.
A camera may be used to acquire a bracket image of the card bracket as described in step S10. Wherein it is ensured that the resolution of the camera is high enough to obtain a clear image.
During the acquisition of the bracket image, the bracket is placed on a platform or background to be photographed and is ensured to be in a stable state, which can be kept stable by using a clamping device or other fixing devices (such as a mechanical arm).
Meanwhile, shooting parameters of the camera, such as focusing, exposure, white balance and the like, are adjusted to acquire high-quality images, namely, uniform illumination conditions are ensured, and the problems of shadow or overexposure and the like are avoided.
Then, a proper angle and a proper distance are selected, and the camera is used for image acquisition so as to ensure that the card support image is complete and clearly visible.
For complex card support bracket structures, multiple shooting angles or cameras can be used to obtain complete bracket images.
Optionally, a top or bottom view of at least one of the card holder brackets is captured to ensure a card holder image is taken from the front.
As described in step S20, an edge detection algorithm is used to identify the boundary of the card support image, where the edge detection algorithm may be Canny algorithm, sobel algorithm, laplacian algorithm, etc. The algorithms can detect strong edges in the image, and parameter adjustment is performed according to the characteristics of the card holder image by selecting a proper edge detection algorithm so as to ensure that the boundary of the card holder is accurately detected.
Optionally, edge connection and filtering may be further performed for the detected receptacle boundary to remove unnecessary edge line segments and noise. The edge connection algorithm (such as the analysis of a connection component) can be used for realizing the connection of edge line segments, connecting adjacent edge line segments into longer edge line segments, and filtering short line segments and noise points through setting limiting conditions such as a threshold value, a connection rule, a length and the like, so that the effective boundary of the card holder is reserved.
Optionally, the position and shape of the card slot are determined according to the detected card holder boundary, which can be identified and determined by the characteristics of the gap, geometry, relative position and the like between the boundary line segments. According to these features, the area range of the card slot can be acquired as the second detection area. And subtracting the second detection area from the area in the card support boundary to obtain the first detection area.
After the first detection area and the second detection area are identified from the card support image, the color card support image is converted into a gray scale image using a gray scale conversion algorithm, as described in step S30.
For example, the card holder image may be loaded into memory using a function, such as imread (), in a suitable image processing library, such as OpenCV. After ensuring that the card holder image has been loaded successfully, the color image may be converted to a grayscale image using the functions provided by the image processing library. In OpenCV, this conversion can be achieved by a cvtColor () function. The color image is converted into a GRAY image by taking the color image as an input image and setting the parameter to cv2.color_bgr2gray.
After the gray level conversion, a single-channel gray level image is obtained. In a gray scale image, the value of each pixel represents the luminance information of that location, typically between 0 and 255, with 0 representing black and 255 representing white.
As described in step S40, based on the preset card support layout, the detailed scheme for detecting the deformation defect of the gray-scale image in the first detection area and the second detection area is as follows:
(1) Deformation defect detection scheme of first detection region:
based on the card support boundary represented by the gray level image in the first detection area, the card support boundary is compared with an ideal card support boundary planned by a preset card support layout, and whether the card support boundary and the ideal card support boundary are consistent is compared, so that possible deformation defects such as shape deviation, rotation, distortion and the like are detected. Wherein the comparison and detection may be implemented using a shape matching algorithm (e.g., hu moment) or a feature matching algorithm based on feature descriptors (e.g., SIFT, ORB, etc.).
(2) Deformation defect detection scheme of second detection region:
based on the boundary of the clamping groove represented by the gray level image in the second detection area, the boundary of the clamping groove is compared with an ideal boundary of the clamping groove planned by a preset clamping bracket layout, so that shape matching (such as Hu moment) and geometric feature analysis are carried out on the boundary of the clamping groove and the boundary of the clamping groove, whether the boundary of the clamping groove and the boundary of the geometric feature analysis are consistent or not is compared, and therefore possible deformation defects such as deformation, size deviation and the like are detected.
The preset card holder layout may be a CAD drawing of the card holder, which includes the geometry and dimensions of the card holder. Such CAD drawings provide accurate card holder layout information that can be used as background images for defect detection.
In addition, the preset card support layout may be a rendering drawing of the CAD drawing. The rendering map is formed by rendering the card holder in CAD software to generate a vivid image. Such an image may provide a more intuitive representation so that an operator may better understand and identify the layout of the card holder.
The CAD drawing or the rendering drawing of the CAD drawing can be used as a reference for presetting the layout of the card tray for comparison with the actual image, thereby finding the deformation defect.
In an embodiment, based on computer vision and image processing technology, the card support boundary and the card slot in the card support bracket are automatically identified, corresponding deformation defect detection is automatically completed, the problems of subjectivity and large error existing in traditional manual detection are overcome, the accuracy and efficiency of deformation defect detection of the card support bracket are improved, and the cost of manual detection is saved.
By using the method to replace manual naked eye detection, even for the card support frame with smaller volume, the high accuracy of deformation defect detection of the card support frame can be still maintained by correspondingly increasing the resolution of the camera.
In an embodiment, based on the above embodiment, the stent image further includes a stopper image; after the step of obtaining the bracket image of the card bracket, the method further comprises the following steps:
identifying feature point locations in the stop image;
determining a third detection area corresponding to the stop part image according to the characteristic point position;
the defect detection method of the card support bracket further comprises the following steps:
and respectively detecting the crush injury defects of the images in the third detection area and the fourth detection area, wherein the fourth detection area is an area in the card support boundary.
In this embodiment, a plurality of cameras may be used to respectively collect the card holder image and the stop portion image of the same card holder bracket; or a camera is adopted to respectively acquire the card support image and the stop part image of the same card support bracket at different moments. Regardless of the manner, the acquired card holder image and the stop portion image need to be associated to the same card holder bracket and serve as the bracket image of the card holder bracket.
The clamping support image is independently used for detecting deformation defects of the clamping support; the stop part image and the card support image can be used for detecting the crush injury defects of different parts of the card support bracket respectively.
Optionally, after the stop image is acquired, feature point detection and matching are performed on the stop image through a computer vision algorithm, so as to determine the positions of key feature points in the image. And calculating and determining the boundary of the relevant area in the stop part image according to the identified characteristic point positions, so as to obtain the position and the range of the third detection area.
Optionally, the feature point is a position of a pinhole of the stopper, and the third detection region is a ring-shaped region (i.e., the stopper is ring-shaped).
Optionally, based on the stop portion image, performing crush injury defect detection on the third detection area: the image in the third detection area is analyzed and processed using image processing and computer vision techniques to detect possible crush defects, which may be identified and located using shape analysis, texture analysis, edge detection, and the like.
Optionally, based on the card support image, performing crush injury defect detection on the image in the fourth detection area: the fourth detection area is an area in the boundary of the card holder, and the image in the area is subjected to detection of the crush injury defect by utilizing image processing and computer vision technology. Shape analysis, texture analysis, edge detection, etc. may also be employed to locate and analyze crush defects.
Optionally, a specific process of performing the crush injury defect detection on the image in the detection area is exemplified as follows:
(1) The color range, the noise reduction coefficient, the difference threshold (used for judging the difference degree between the defect area and the surrounding area), the area threshold (used for screening out the defect parts with the area meeting the requirement), the length threshold (used for filtering out the linear defects with the length not meeting the requirement) and the like of the crush defects to be detected are preset.
(2) And performing image processing and analysis on the image in the detection area by using the set defect colors, the noise reduction coefficient, the difference threshold, the area threshold and the length threshold.
And extracting a sub-region matched with the color range from the image according to the set defect color range to obtain a potential defect region. Then, the image is subjected to noise reduction processing using the noise reduction coefficient to reduce the influence of noise.
And/or applying a difference threshold, marking the sub-region with a difference value exceeding the threshold as a potential defect region.
And screening out a defect area meeting the requirements according to the set area threshold value and the length threshold value. And finally, further analyzing and detecting according to morphological characteristics, texture attributes and the like of the region, and identifying and positioning the crush injury defects.
Therefore, the corresponding crush defect detection can be automatically carried out on the clamping support and the stopping part on the clamping support bracket.
In an embodiment, after the step of performing the crush defect detection on the images in the third detection area and the fourth detection area respectively, the method further includes:
converting the stent image into a binarized image;
and respectively carrying out scratch defect detection and/or plaque defect detection on the binarized images in the third detection area and the fourth detection area.
In this embodiment, after the crush defect detection step, the stent image (including the card support image and the stopper image) is subjected to binarization processing to generate a corresponding binarized image. Based on the segmentation by the threshold, pixel values in the image are converted into a binary image, where a pixel value of 0 represents the background and a pixel value of 1 represents the foreground (stent region).
When the scratch defects are detected on the binarized images in the third detection area and the fourth detection area, the methods of edge detection, morphological processing and the like can be used for detecting and positioning the possible scratch defects such as protruding edges, obvious traces, surface scratch defects and the like on the binarized images.
When detecting plaque defects on the binarized images in the third detection area and the fourth detection area, plaque defects possibly existing, such as abnormal shapes, color changes and the like, can be detected and positioned on the binarized images by utilizing technologies such as area segmentation, texture analysis and the like.
The defect detection flow of the card support bracket can be further perfected by converting the bracket image into a binarized image and respectively carrying out scratch defect detection and/or plaque defect detection on the binarized images in the third detection area and the fourth detection area, and different types of defects are comprehensively considered for analysis and positioning.
In an embodiment, on the basis of the foregoing embodiment, the defect detection method of the card support bracket further includes:
when detecting that the card support bracket has defects, marking corresponding defects in the bracket image by using preset colors.
In this embodiment, if at least one of deformation, crush injury, scratch and plaque defect is detected in the stent image, a corresponding defect area of the stent is identified and positioned, and the detected defect is marked in the stent image, which can be achieved by a method of drawing or overlaying a preset color at the defect area.
Wherein a predetermined color, such as red or other striking color, is selected, and the defective area is marked on the image with the color to form a marked area mark so that an operator can intuitively recognize the problem of the defective area.
In an embodiment, on the basis of the foregoing embodiment, the defect detection method of the card support bracket further includes:
when the bracket image is acquired, controlling a mechanical arm clamping the camera to adjust the shooting angle of the camera when the camera is controlled to acquire the card bracket image, so that the camera can continuously acquire the stop part image;
or when the camera is controlled to acquire the image of the stop part, controlling the mechanical arm clamping the camera to adjust the shooting angle of the camera so that the camera can continuously acquire the card support image.
In this embodiment, when the bracket image is collected, according to the type of the image collected by the camera, the shooting angle of the camera may be adjusted by controlling the mechanical arm for clamping the camera, so as to continuously collect the required stop portion image or the card support image.
Optionally, when putting the card support in the image acquisition area of camera, can be earlier with the card support front in the card support towards the camera, control the camera and gather card support image, then control the arm adjustment camera of centre gripping camera shooting angle, make it continue to gather required backstop portion image. The adjusted camera angle can ensure that the image information of the stop part can be acquired, so that subsequent processing such as feature point positioning and defect detection can be performed.
Or when the clamping support is placed in the image acquisition area of the camera, the front surface of the stopping part in the clamping support can face the lens, and when the camera acquires the image of the stopping part, the mechanical arm for clamping the camera is controlled to adjust the shooting angle of the camera, so that the camera can continuously acquire the required clamping image. The adjusted camera angle can ensure that the image information of the card support part can be acquired so as to carry out subsequent card support defect detection processing.
Therefore, the shooting angle of the camera is adjusted according to the type of the current acquired image, so that the camera can be ensured to automatically acquire the required stop part image and the card support image, further follow-up defect detection and analysis are performed, and the efficiency of the bracket image acquisition process is improved.
In an embodiment, on the basis of the foregoing embodiment, the defect detection method of the card support bracket further includes:
when the bracket image is acquired, when the camera is controlled to acquire the card bracket image, the mechanical arm supporting the card bracket is controlled to align the stop part of the card bracket to the lens of the camera so as to enable the front of the camera to acquire the stop part image;
or when the camera is controlled to acquire the image of the stop part, the mechanical arm supporting the card support bracket is controlled to align the card support of the card support bracket to the lens of the camera, so that the front of the camera acquires the image of the card support.
In this embodiment, when the bracket image is acquired, according to the type of the image acquired by the camera, the stop portion of the bracket or the bracket of the bracket can be aligned to the lens of the camera by controlling the mechanical arm supporting the bracket of the bracket, so that the front of the camera acquires the required stop portion image or the bracket image.
Optionally, when the mechanical arm supporting the card support bracket places the card support bracket in the image acquisition area of the camera, the front surface of the card support in the card support bracket faces towards the lens, and then the camera is controlled to acquire the card support image. When the camera collects the card support image, the mechanical arm supporting the card support bracket is controlled, and the position of the card support bracket is adjusted, so that the stop part of the card support bracket is aligned with the lens of the camera. At this time, the camera faces the stop part, and acquires the required image of the stop part from the front for subsequent defect detection processing.
Or when the mechanical arm for supporting the clamping support is controlled to place the clamping support in the image acquisition area of the camera, the front surface of the stopping part in the clamping support faces towards the lens, and then the camera is controlled to acquire the image of the stopping part. And then controlling a mechanical arm supporting the clamping support to adjust the position of the clamping support, and aligning the clamping support of the clamping support with the lens of the camera. At this time, the camera faces the card holder part, and the required card holder image can be collected on the front surface so as to perform subsequent card holder defect detection processing.
The mechanical arm supporting the clamping support is controlled, the stopping part or the clamping support of the clamping support is aligned to the lens of the camera, so that the front face of the camera can be ensured to acquire the required image of the stopping part or the clamping support image, the subsequent defect detection and analysis are supported, and the efficiency of the support image acquisition process is improved.
In addition, referring to fig. 2, in an embodiment of the present application, there is further provided a defect detecting device Z10, including:
the image acquisition module Z11 is used for acquiring a bracket image of the card bracket, wherein the bracket image at least comprises a card bracket image; the card support comprises a card support and a stop part arranged on the side face of the card support, wherein a card slot is arranged in the card support and is used for placing a SIM card or a memory card;
the area identifying module Z12 is used for carrying out edge detection on the card holder image so as to identify a first detection area and a second detection area, wherein the first detection area comprises a card holder boundary, and the second detection area is a card slot area;
the image conversion module Z13 is used for converting the card support image into a gray image;
and the defect detection module Z14 is used for respectively carrying out deformation defect detection on the gray level images in the first detection area and the second detection area based on a preset card support layout.
Alternatively, the defect detecting device may be a virtual control device (such as a virtual machine), or may be a physical device (such as a physical device other than a computer device that may perform the corresponding method).
In addition, the embodiment of the application also provides a computer device, and the internal structure of the computer device can be shown in fig. 3. The computer device includes a processor, a memory, a communication interface, and a database connected by a system bus. Wherein the processor is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The database of the computer device is used to store data of computer program calls. The communication interface of the computer device is used for data communication with an external terminal. The input device of the computer device is used for receiving signals input by external equipment. The computer program is executed by a processor to implement a method of defect detection for a card holder bracket as described in the above embodiments.
It will be appreciated by those skilled in the art that the architecture shown in fig. 3 is merely a block diagram of a portion of the architecture in connection with the present inventive arrangements and is not intended to limit the computer devices to which the present inventive arrangements are applicable.
Furthermore, the present application also proposes a computer-readable storage medium comprising a computer program which, when executed by a processor, implements the steps of the defect detection method of a card holder bracket as described in the above embodiments. It is understood that the computer readable storage medium in this embodiment may be a volatile readable storage medium or a nonvolatile readable storage medium.
In summary, in the defect detection method, the defect detection device, the computer equipment and the computer readable storage medium for the card support bracket provided by the embodiment of the application, based on computer vision and image processing technology, the card support boundary and the card slot in the card support bracket are automatically identified, and corresponding deformation defect detection is automatically completed, so that the problems of high subjectivity and error in the traditional manual inspection are overcome, the accuracy and efficiency of deformation defect detection for the card support bracket are improved, and the cost of manual detection is saved.
Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium provided by the present application and used in embodiments may include non-volatile and/or volatile memory. The nonvolatile memory can include Read Only Memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual speed data rate SDRAM (SSRSDRAM), enhanced SDRAM (ESDRAM), synchronous Link DRAM (SLDRAM), memory bus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), among others.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, apparatus, article, or method that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, apparatus, article, or method. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, apparatus, article or method that comprises the element.
The foregoing description is only of the preferred embodiments of the present application and is not intended to limit the scope of the application, and all equivalent structures or equivalent processes using the descriptions and drawings of the present application or direct or indirect application in other related technical fields are included in the scope of the present application.

Claims (10)

1. The defect detection method of the card support bracket is characterized in that the card support bracket comprises a card support and a stop part arranged on the side surface of the card support; the card holder is provided with a card slot, and the card slot is used for placing a SIM card or a memory card; the defect detection method of the card support bracket comprises the following steps:
acquiring a bracket image of a card bracket, wherein the bracket image at least comprises a card bracket image;
performing edge detection on the card support image to identify a first detection area and a second detection area, wherein the first detection area comprises a card support boundary, and the second detection area is a card slot area;
converting the card support image into a gray image;
and respectively detecting deformation defects of the gray images in the first detection area and the second detection area based on a preset card support layout.
2. The method for detecting defects of a card holder bracket according to claim 1, wherein the bracket image further includes a stopper image; after the step of obtaining the bracket image of the card bracket, the method further comprises the following steps:
identifying feature point locations in the stop image;
determining a third detection area corresponding to the stop part image according to the characteristic point position;
the defect detection method of the card support bracket further comprises the following steps:
and respectively detecting the crush injury defects of the images in the third detection area and the fourth detection area, wherein the fourth detection area is an area in the card support boundary.
3. The method for detecting defects of a card holder according to claim 2, wherein the characteristic point is a position of a stopper pinhole, and the third detection region is a ring-shaped region.
4. The method for detecting defects of a card holder according to claim 2, wherein after the step of performing crush defect detection on the images in the third detection area and the fourth detection area, respectively, the method further comprises:
converting the stent image into a binarized image;
and respectively carrying out scratch defect detection and/or plaque defect detection on the binarized images in the third detection area and the fourth detection area.
5. The method for detecting defects of a card holder as claimed in any one of claims 1 to 4, further comprising:
when detecting that the card support bracket has defects, marking corresponding defects in the bracket image by using preset colors.
6. The method for detecting defects of a card holder as claimed in claim 2, further comprising:
when the bracket image is acquired, controlling a mechanical arm clamping the camera to adjust the shooting angle of the camera when the camera is controlled to acquire the card bracket image, so that the camera can continuously acquire the stop part image;
or when the camera is controlled to acquire the image of the stop part, controlling the mechanical arm clamping the camera to adjust the shooting angle of the camera so that the camera can continuously acquire the card support image.
7. The method for detecting defects of a card holder as claimed in claim 2, further comprising:
when the bracket image is acquired, when the camera is controlled to acquire the card bracket image, the mechanical arm supporting the card bracket is controlled to align the stop part of the card bracket to the lens of the camera so as to enable the front of the camera to acquire the stop part image;
or when the camera is controlled to acquire the image of the stop part, the mechanical arm supporting the card support bracket is controlled to align the card support of the card support bracket to the lens of the camera, so that the front of the camera acquires the image of the card support.
8. A defect detection apparatus, comprising:
the image acquisition module is used for acquiring a bracket image of the card bracket, wherein the bracket image at least comprises a card bracket image; the card support comprises a card support and a stop part arranged on the side face of the card support, wherein a card slot is arranged in the card support and is used for placing a SIM card or a memory card;
the area identification module is used for carrying out edge detection on the card support image so as to identify a first detection area and a second detection area, wherein the first detection area comprises a card support boundary, and the second detection area is a card slot area;
the image conversion module is used for converting the card support image into a gray image;
and the defect detection module is used for respectively carrying out deformation defect detection on the gray level images in the first detection area and the second detection area based on a preset card support layout.
9. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, which when executed by the processor performs the steps of the method of defect detection of a card holder support according to any one of claims 1 to 7.
10. A computer-readable storage medium, wherein a computer program is stored on the computer-readable storage medium, which when executed by a processor, implements the steps of the defect detection method of a card holder bracket according to any one of claims 1 to 7.
CN202311356994.6A 2023-10-19 2023-10-19 Defect detection method and device for card support bracket, computer equipment and storage medium Pending CN117132586A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202311356994.6A CN117132586A (en) 2023-10-19 2023-10-19 Defect detection method and device for card support bracket, computer equipment and storage medium

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202311356994.6A CN117132586A (en) 2023-10-19 2023-10-19 Defect detection method and device for card support bracket, computer equipment and storage medium

Publications (1)

Publication Number Publication Date
CN117132586A true CN117132586A (en) 2023-11-28

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