CN113039577A - Product testing method and device, computer readable storage medium and electronic equipment - Google Patents
Product testing method and device, computer readable storage medium and electronic equipment Download PDFInfo
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Abstract
A product reliability testing method, a device, a storage medium and an electronic device are provided. The method comprises the steps of collecting a first image of a standard product, wherein the first image comprises a first positioning piece and a plurality of first reference pieces with color marks, and the first reference pieces are provided with preset gray value ranges (S201); collecting a second image of the product to be detected, wherein the second image comprises a second positioning part which is a product component corresponding to the first positioning part in the second image (S202); establishing an affine relation between the first image and the second image according to the first positioning piece and the second positioning piece (S203); affine the area of the first reference piece to the second image according to the affine relation to obtain a first to-be-detected area corresponding to the area where the first reference piece is located in the second image (S204); converting an image of a first region to be detected into a tone gray image, and acquiring a first gray value of each pixel point in the tone gray image (S205); and when the total pixel area of the pixel points of which the first gray value is within the preset gray value range is larger than the first threshold value, judging that the first to-be-detected piece of the to-be-detected product is installed qualified (S206). The method has high efficiency and high accuracy.
Description
Technical Field
The application belongs to the field of product testing, and particularly relates to a method and a device for testing product reliability, a computer-readable storage medium and electronic equipment.
Background
With the development of electric vehicles, the assembly requirements for Alternating current/Direct current (AC/DC) converters are becoming higher and higher. At present, whether the assembly of the AC/DC converter meets the requirements or not is judged mostly through manual work or semi-manual work, the detection efficiency is low, and mistakes are easy to make.
Disclosure of Invention
In view of this, the embodiments of the present application provide a method for testing product reliability, which has high detection accuracy and high efficiency.
The application provides a product reliability testing method, which comprises the following steps:
the method comprises the steps of collecting a first image of a standard product, wherein the first image comprises a first positioning piece and a plurality of first reference pieces with color marks, and the first reference pieces have preset gray value ranges;
acquiring a second image of the product to be detected, wherein the second image comprises a second positioning piece which is a product component corresponding to the first positioning piece in the second image;
establishing an affine relation between the first image and the second image according to the first positioning piece and the second positioning piece;
affine the area of the first reference piece to a second image according to the affine relation so as to obtain a first to-be-detected area corresponding to the area where the first reference piece is located in the second image;
converting the image of the first region to be detected into a tone gray image, and acquiring a first gray value of each pixel point in the tone gray image;
and when the total pixel area of the pixel points of which the first gray value is within the preset gray value range is larger than a first threshold value, judging that the first to-be-detected piece of the to-be-detected product is qualified to install.
Further, establishing an affine relationship between the first image and the second image according to the first positioning element and the second positioning element specifically includes:
and establishing an affine relation between the first image and the second image according to the relative position or the coordinate of the first positioning part in the first image and the relative position or the coordinate of the second positioning part in the second image.
Further, the converting the image of the first region to be detected into a tone gray image specifically includes:
splitting the image of the first region to be detected into a red gray image, a blue gray image and a green gray image;
and converting the red gray image, the blue gray image and the green gray image into tone gray images.
Further, the first image further includes a plurality of second reference features having shape features, the method further comprising:
affine the area of the second reference piece to a second image according to the affine relation so as to obtain a second to-be-detected area corresponding to the area where the second reference piece is located in the second image;
and when the number of the second to-be-detected pieces in the second to-be-detected area, the shape matching degree of which with the second reference piece is greater than or equal to a second threshold value, is equal to the number of the second reference pieces of the first image, judging that the second to-be-detected pieces of the to-be-detected product are installed qualified.
The present application further provides a product reliability testing device, which includes:
the image acquisition module is used for acquiring a first image of a standard product, wherein the first image comprises a first positioning piece and a plurality of first reference pieces with color marks, and the first reference pieces have preset gray value ranges;
the image acquisition module is also used for acquiring a second image of the product to be detected, the second image comprises a second positioning piece, and the second positioning piece is a product component corresponding to the first positioning piece in the second image;
the affine construction module is used for establishing an affine relation between the first image and the second image according to the first positioning piece and the second positioning piece;
the affine module is used for affine matching the area of the first reference piece to the second image according to the affine relation so as to obtain a first to-be-detected area corresponding to the area where the first reference piece is located in the second image;
the image conversion module is used for converting the image of the first region to be detected into a tone gray image and acquiring a first gray value of each pixel point in the tone gray image;
and the analysis processing module is used for judging that the first to-be-detected piece of the to-be-detected product is installed qualified when the total pixel area of the pixel points of which the first gray value is within the preset gray value range is larger than a first threshold value.
Further, the affine module is specifically configured to establish an affine relationship between the first image and the second image according to the relative position or coordinate of the first positioning element in the first image and the relative position or coordinate of the second positioning element in the second image.
Further, the image conversion module includes:
the first conversion module is used for splitting the image of the first region to be detected into a red gray image, a blue gray image and a green gray image;
and the second conversion module is used for converting the red gray image, the blue gray image and the green gray image into a tone gray image.
Further, the first image further comprises a plurality of second reference members having shape features;
the affine module is further configured to affine the region of the second reference piece to the second image according to the affine relation, so as to obtain a second to-be-detected region in the second image, which corresponds to the region where the second reference piece is located;
the analysis processing module is further configured to determine that the second to-be-detected pieces of the to-be-detected product are installed qualified when the number of the second to-be-detected pieces in the second to-be-detected area, which have a shape matching degree with the second reference piece that is greater than or equal to a second threshold value, is equal to the number of the second reference pieces of the first image.
The present application also provides a computer-readable storage medium storing computer-executable program code for causing a computer to perform the product reliability testing method described above.
The present application further provides an electronic device, comprising:
a processor and a memory electrically connected to the processor, the memory storing program code executable by the processor, the program code when invoked and executed by the processor performing the product reliability testing method of the preceding claims.
Therefore, the product reliability testing method firstly sets the first image of the standard product, then collects the second image of the product to be tested, compares the second image of the product to be tested with the first image, and judges whether the product to be tested is qualified. The traditional manual and semi-manual judging mode is replaced, the testing efficiency is high, and the accuracy is high.
Drawings
To more clearly illustrate the structural features and effects of the present application, a detailed description is given below in conjunction with the accompanying drawings and specific embodiments.
Fig. 1 is a schematic structural diagram of a product image acquisition device used in an embodiment of the present application.
Fig. 2 is a flowchart of a product reliability testing method according to an embodiment of the present application.
Fig. 3 is a flowchart of a product reliability testing method according to another embodiment of the present application.
Fig. 4 is a schematic structural diagram of a product reliability testing apparatus according to an embodiment of the present application.
Fig. 5 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
DETAILED DESCRIPTION OF EMBODIMENT (S) OF INVENTION
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. It should be apparent that the described embodiments are only some of the embodiments of the present application, and not all embodiments. All other embodiments that can be derived by a person skilled in the art from the embodiments given herein without making any creative effort shall fall within the protection scope of the present application.
Referring to fig. 1, fig. 1 is a product image capturing device 100 according to an embodiment of the present application, which includes a frame 10, a camera 20, a light source 30, a host 40, and a display 50. The camera 20 is installed on the frame 10, and is used for shooting color images of a standard product and a product to be detected and transmitting the color images to the host computer 40, specifically, when shooting, a camera of the camera 20 is aligned with the product to be detected on the production line. The light source 30 is disposed on the frame 10 at a position adjacent to the camera 20 for improving the brightness of the environment photographed by the camera 20 to improve the color image quality. The host computer 40 is used to install product inspection software for performing product reliability tests of the embodiments described below in the present application. The display 50 is electrically connected to the host computer 40 for displaying the test result of the host computer 40.
Referring to fig. 2, an embodiment of the first aspect of the present application provides a method for testing product reliability, which is used to detect whether a wiring harness and a screw of an AC/DC converter are accurately installed, and includes:
s201, collecting a first image of a standard product, wherein the first image comprises a first positioning piece and a plurality of first reference pieces with color marks, and the first reference pieces have a preset gray value range.
Specifically, a first image of the standard product is acquired through the camera 20, a component with a unique feature is selected from the first image to serve as a first positioning piece, a first to-be-detected piece with a color identifier, which is installed in a standard mode, is acquired to serve as a first reference piece, and a preset gray value range of the first reference piece and a relative position or a coordinate of the first positioning piece in the first image are acquired. Wherein the first image is a color image. Specifically, when the colors of the first reference elements are different, the preset gray scale value ranges thereof are correspondingly different, for example, when the color of the first portion to be detected is red, the preset gray scale value range is between 245-255; when the color of the first part to be detected is black, the preset gray value range is 0-15; when the color of the first portion to be detected is blue, the preset gray value range is between 145 and 155; when the color of the first portion to be detected is yellow, the preset gray value range is 37-50. In one embodiment, the first object to be detected is a wire harness.
The gray value is also called brightness value, because the color and brightness of each point of the scene are different, each point on the shot black-and-white picture or black-and-white image reproduced by the television receiver presents different gray. The logarithmic relationship between white and black is divided into several levels, called "gray scale". The gray scale values typically range from 0 to 255, with white (i.e., all bright) being 255 and black (i.e., all dark) being 0.
S202, collecting a second image of the product to be detected, wherein the second image comprises a second positioning piece, and the second positioning piece is a product component corresponding to the first positioning piece in the second image.
Specifically, a second image of the product to be detected on the production line is acquired by using the camera 20, the second image is a color image, and a product component, the matching degree of which with the first positioning member reaches a preset value (for example, 0.5, 0.6, 0.7, 0.8, 0.9, etc.), is acquired in the second image and is used as a second positioning member. In addition, the second image also comprises a part where the first to-be-detected piece to be judged is installed. Specifically, this step further includes acquiring a relative position or coordinate of the second positioning element in the second image.
S203, establishing an affine relation between the first image and the second image according to the first positioning piece and the second positioning piece.
Specifically, an affine relationship between the first image and the second image is established according to the relative position or coordinate of the first positioning element in the first image and the relative position or coordinate of the second positioning element in the second image. The affine matrix is established, so that the judgment error caused by the deviation of the acquired image can be better avoided during image acquisition, and the accuracy of product testing is improved.
And S204, affine matching the region of the first reference piece to the second image according to the affine relation so as to obtain a first region to be detected corresponding to the region where the first reference piece is located in the second image.
And affine matching is carried out on the area where the first reference piece is located to the second image according to the affine relation between the first positioning piece and the second positioning piece, so that a first to-be-detected area corresponding to the area where the first reference piece is located in the second image is obtained. The area of the first reference piece is affine to the second image, so that the first piece to be detected can be more accurately positioned, the detection range of the first piece to be detected is narrowed, and the detection efficiency and the test accuracy are improved.
S205, converting the image of the first region to be detected into a tone gray image, and acquiring a first gray value of each pixel point in the tone gray image.
Specifically, converting the image of the first region to be detected into a tone gray image specifically includes:
s2051, splitting the image of the first area to be detected into a red gray image, a blue gray image and a green gray image;
specifically, the second image is converted into a red grayscale image, a blue grayscale image, and a green grayscale image using the analog signal of the BT601 standard. The BT601 standard is a standard definition international definition that includes analog signals and digital signals.
"grayscale image" refers to an image having only one sample color per pixel, typically displayed as a grayscale from the darkest black to the brightest white, with the grayscale image having many more levels of color depth between black and white.
S2052, converting the red, blue, and green grayscale images into tone grayscale images.
Specifically, an HSV color space is adopted to convert the red, blue, and green grayscale images into a tone grayscale image, and the specific calculation formula is as follows:
max (R, G, B) ═ Min (R, G, B), h ═ 0 °;
max (R, G, B) ═ R and G ≧ B, h ═ 60 ° × (G-B) ÷ [ Max (R, G, B) -Min (R, G, B) ] +0 °;
max (R, G, B) ═ R and G is less than B, h ═ 60 ° × (G-B) ÷ [ Max (R, G, B) -Min (R, G, B) ] +360 °;
max (R, G, B) ═ G, h ═ 60 ° × (B-R) ÷ [ Max (R, G, B) -Min (R, G, B) ] +120 °;
max (R, G, B) ═ B, h ═ 60 ° × (R-G) ÷ [ Max (R, G, B) -Min (R, G, B) ] +240 °;
where h is the tone of the tone gray image, R represents the gray level value of the red gray image, G represents the gray level value of the green gray image, and B represents the gray level value of the blue gray image.
Hsv (hue validation value) is a color space created according to the intuitive nature of color, also known as the hexagonal cone Model (Hexcone Model). The parameters of the color in this model are Hue (Hue, H), Saturation (Saturation, S), and lightness (Value, V), respectively.
S206, when the total pixel area of the pixel points of which the first gray value is within the preset gray value range is larger than a first threshold value, judging that the first to-be-detected piece of the to-be-detected product is installed qualified.
Specifically, a first region to be detected in the tone gray image is cut. And extracting a pixel region with a gray value within a preset gray value range from the cut tone gray image, calculating the pixel area of the pixel region, and if the pixel area is larger than a first threshold value, installing a first to-be-detected piece of the product to be detected to be qualified, otherwise, installing the first to-be-detected piece to be unqualified and needing to be installed again.
More specifically, a threshold segmentation method is adopted to extract a pixel area of which the gray value is within a preset gray value range in the tone gray image, for example, if the color of the first to-be-detected piece is red, a pixel area of which the gray value is between 245 and 255 in the tone gray image is extracted; and calculating the pixel area of the pixel area, and when the pixel area is larger than a first threshold value, the first to-be-detected piece is installed qualified. And if the color of the first to-be-detected piece is black, extracting a pixel area with the gray value between 0 and 15 in the tone gray image. If the color of the first to-be-detected piece is blue, a pixel area between the gray values of 145-155 in the tone gray image is extracted. And if the color of the first to-be-detected piece is yellow, extracting a pixel area with the gray value of 37-50 in the tone gray image.
The threshold segmentation method is an image segmentation technology based on regions, and can greatly compress data volume and simplify the analysis and processing steps of images by dividing image pixel points into a plurality of classes according to gray levels.
In some embodiments, the first threshold may be any value between 0.5-0.9, such as 0.5, 0.6, 0.7, 0.8, 0.9, and the like.
The product reliability testing method comprises the steps of firstly acquiring a first image of a standard product, acquiring a first positioning piece and a first reference piece of the first image, then acquiring a second image of a product to be tested, comparing the second image with the first image, and judging whether the product to be tested is qualified. The traditional manual and semi-manual judging mode is replaced, the testing efficiency is high, and the accuracy is high.
Referring to fig. 3, another embodiment of the present application provides a method for testing product reliability, including:
s301, collecting a first image of a standard product, wherein the first image comprises a first positioning piece, a plurality of first reference pieces with color marks and a plurality of second reference pieces with shape characteristics, and the first reference pieces have a preset gray value range;
specifically, a first image of a standard product is acquired through the camera 20, a part with a unique feature is selected from the first image to serve as a first positioning piece, a first to-be-detected piece with a color identifier, which is installed in a standard mode, is acquired to serve as a first reference piece, a preset gray value range of the first reference piece and a relative position or coordinate of the first positioning piece in the first image are acquired, and a second reference piece with a shape feature is acquired. Wherein the first image is a color image. Specifically, when the colors of the first reference elements are different, the preset gray scale value ranges thereof are correspondingly different, for example, when the color of the first portion to be detected is red, the preset gray scale value range is between 245-255; when the color of the first part to be detected is black, the preset gray value range is 0-15; when the color of the first portion to be detected is blue, the preset gray value range is between 145 and 155; when the color of the first portion to be detected is yellow, the preset gray value range is 37-50. In one embodiment, the first object to be detected is a wire harness.
S302, collecting a second image of the product to be detected, wherein the second image comprises a second positioning piece which is a product component corresponding to the first positioning piece in the second image;
for a detailed description, refer to the above embodiments, which are not repeated herein.
S303, establishing an affine relation between the first image and the second image according to the first positioning piece and the second positioning piece;
when the first to-be-detected piece needs to be tested, S304 is executed, and when the second to-be-detected piece needs to be tested, S307 is executed.
For a detailed description, refer to the above embodiments, which are not repeated herein.
S304, affine the region of the first reference piece to the second image according to the affine relation to obtain a first to-be-detected region corresponding to the region where the first reference piece is located in the second image;
for a detailed description, refer to the above embodiments, which are not repeated herein.
S305, converting the image of the first region to be detected into a tone gray image, and acquiring a first gray value of each pixel point in the tone gray image;
for a detailed description, refer to the above embodiments, which are not repeated herein.
S306, when the total pixel area of the pixel points of which the first gray value is within the preset gray value range is larger than a first threshold value, judging that a first to-be-detected piece of the to-be-detected product is installed qualified;
for a detailed description, refer to the above embodiments, which are not repeated herein.
S307, affine the region of the second reference piece to the second image according to the affine relation to obtain a second to-be-detected region corresponding to the region of the second reference piece in the second image;
and affine matching the area where the second reference piece is located to the second image according to the affine relation established in the step S303, so as to obtain a second to-be-detected area corresponding to the area where the second reference piece is located in the second image. The area of the second reference piece is affine to the second image, so that the second piece to be detected can be more accurately positioned, the detection range of the second piece to be detected is reduced, and the detection efficiency and the test accuracy are improved.
In one embodiment, the second object to be detected is a screw, and it is required to detect whether the screw is mounted or not and whether the shape of the mounted screw is accurate or not.
S308, when the number of the second to-be-detected pieces in the second to-be-detected area, which has the shape matching degree with the second reference piece larger than or equal to the second threshold value, is equal to the number of the second reference pieces of the first image, it is determined that the second to-be-detected pieces of the to-be-detected product are installed qualified.
Specifically, by adopting a shape matching method, second to-be-detected pieces with a shape matching degree exceeding a second threshold value with a second reference piece are searched one by one in the second to-be-detected area, and when the number of the second to-be-detected pieces with the shape matching degree exceeding the second threshold value with the second reference piece is equal to the number of the second reference pieces of the first image, it is determined that the second to-be-detected pieces of the to-be-detected product are installed qualified. On the contrary, when the number of the second reference pieces with the shape matching degree larger than the second threshold is not equal to the number of the second reference pieces of the first image, the second to-be-detected piece of the to-be-detected product is judged to be unqualified to be installed, and the unqualified number and position are displayed in the display 50, so that the unqualified to-be-installed product can be installed again.
In some embodiments, the second threshold may be any value between 0.5-0.9, such as 0.5, 0.6, 0.7, 0.8, 0.9, and the like.
Referring to fig. 4, a second aspect of the present application provides a product reliability testing apparatus 300, which includes:
the image acquisition module 310 is configured to acquire a first image of a standard product, where the first image includes a first positioning element and a plurality of first reference elements with color identifiers, and the first reference elements have a preset gray value range;
the image acquisition module 310 is further configured to acquire a second image of the product to be detected, where the second image includes a second positioning element, and the second positioning element is a product component corresponding to the first positioning element in the second image;
the affine construction module 320 is configured to establish an affine relationship between the first image and the second image according to the first positioning element and the second positioning element;
the affine module 330 is configured to affine the region of the first reference component to the second image according to the affine relationship, so as to obtain a first to-be-detected region in the second image, where the first to-be-detected region corresponds to the region where the first reference component is located;
the image conversion module 340 is configured to convert the image of the first region to be detected into a tone gray image, and obtain a first gray value of each pixel in the tone gray image;
and the analysis processing module 350 is configured to determine that the first to-be-detected piece of the to-be-detected product is installed qualified when the total pixel area of the pixel points of which the first gray value is within the preset gray value range is larger than a first threshold.
For a detailed description, please refer to the specific description of the product reliability testing method in the embodiments of the present application, which is not repeated herein.
In some embodiments, the affine module 330 is specifically configured to establish an affine relationship between the first image and the second image according to the relative position or coordinate of the first positioning element in the first image and the relative position or coordinate of the second positioning element in the second image.
In some embodiments, the image conversion module 340 includes:
a first conversion module 341, configured to convert the image of the first region to be detected into a red grayscale image, a blue grayscale image, and a green grayscale image;
a second conversion module 342, configured to convert the red grayscale image, the blue grayscale image, and the green grayscale image into a tone grayscale image.
In some embodiments, the first image further comprises a plurality of second reference features having shape features;
the affine module 330 is further configured to affine the region of the second reference to the second image according to the affine relationship, so as to obtain a second to-be-detected region in the second image, which corresponds to the region where the second reference is located;
the analysis processing module 350 is further configured to determine that the second to-be-detected pieces of the to-be-detected product are installed qualified when the number of the second to-be-detected pieces in the second to-be-detected area, which has a shape matching degree with the second reference piece that is greater than or equal to a second threshold value, is equal to the number of the second reference pieces of the first image.
For a detailed description, please refer to the specific description of the product reliability testing method in the embodiments of the present application, which is not repeated herein.
A third aspect of the present application provides a computer-readable storage medium storing computer-executable program code for causing a computer to execute the product reliability testing method of the above-described embodiment of the present application.
Referring to fig. 5, in a fourth aspect, the present invention provides an electronic device 400, which includes a processor 410 and a memory 430 electrically connected to the processor 410, wherein the memory 430 stores program codes executable by the processor 410, and when the program codes are called and executed by the processor 410, the product reliability testing method of the above embodiment is performed.
The memory 430 is a non-volatile computer-readable storage medium, and can be used for storing non-volatile software programs, non-volatile computer-executable programs, and modules, such as program instructions/modules corresponding to the image local shading processing method in the embodiment of the present application. The processor 410 executes various functional applications of the server and data processing by executing nonvolatile software programs, instructions and modules stored in the memory 430, namely, implements the product reliability testing method of the above-mentioned method embodiment.
May include Random Access Memory (RAM), Read-Only Memory (ROM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Compact disk Read-Only Memory (CD-ROM) or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer. Furthermore, the method is simple. Any connection is properly termed a computer-readable medium. For example, if software is transmitted from a website, a server, or other remote source using a coaxial cable, a fiber optic cable, a twisted pair, a Digital Subscriber Line (DSL), or wireless technologies such as infrared, radio, and microwave, the coaxial cable, the fiber optic cable, the twisted pair, the DSL, or the wireless technologies such as infrared, radio, and microwave are included in the fixation of the medium. Disk and disc, as used herein, includes Compact Disc (CD), laser disc, optical disc, Digital Versatile Disc (DVD), floppy Disk and blu-ray disc where disks usually reproduce data magnetically, while discs reproduce data optically with lasers. Combinations of the above should also be included within the scope of computer-readable media.
The above description is only for the specific embodiments of the present application, but the scope of the present application is not limited thereto, and any person skilled in the art can easily conceive various equivalent modifications or substitutions within the technical scope of the present application, and these modifications or substitutions should be covered by the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
Claims (10)
1. A method for testing product reliability, comprising:
the method comprises the steps of collecting a first image of a standard product, wherein the first image comprises a first positioning piece and a plurality of first reference pieces with color marks, and the first reference pieces have preset gray value ranges;
acquiring a second image of the product to be detected, wherein the second image comprises a second positioning piece which is a product component corresponding to the first positioning piece in the second image;
establishing an affine relation between the first image and the second image according to the first positioning piece and the second positioning piece;
affine the area of the first reference piece to a second image according to the affine relation so as to obtain a first to-be-detected area corresponding to the area where the first reference piece is located in the second image;
converting the image of the first region to be detected into a tone gray image, and acquiring a first gray value of each pixel point in the tone gray image;
and when the total pixel area of the pixel points of which the first gray value is within the preset gray value range is larger than a first threshold value, judging that the first to-be-detected piece of the to-be-detected product is qualified to install.
2. The method for testing the reliability of a product according to claim 1, wherein the establishing an affine relationship between the first image and the second image according to the first positioning element and the second positioning element specifically comprises:
and establishing an affine relation between the first image and the second image according to the relative position or the coordinate of the first positioning part in the first image and the relative position or the coordinate of the second positioning part in the second image.
3. The method for testing the product reliability according to claim 1, wherein the converting the image of the first region to be detected into a tone gray image specifically comprises:
splitting the image of the first region to be detected into a red gray image, a blue gray image and a green gray image;
and converting the red gray image, the blue gray image and the green gray image into tone gray images.
4. The product reliability test method of any one of claims 1 to 3, wherein the first image further comprises a plurality of second reference pieces having shape features, the method further comprising:
affine the area of the second reference piece to a second image according to the affine relation so as to obtain a second to-be-detected area corresponding to the area where the second reference piece is located in the second image;
and when the number of the second to-be-detected pieces in the second to-be-detected area, the shape matching degree of which with the second reference piece is greater than or equal to a second threshold value, is equal to the number of the second reference pieces of the first image, judging that the second to-be-detected pieces of the to-be-detected product are installed qualified.
5. A product reliability testing apparatus, comprising:
the image acquisition module is used for acquiring a first image of a standard product, wherein the first image comprises a first positioning piece and a plurality of first reference pieces with color marks, and the first reference pieces have preset gray value ranges;
the image acquisition module is also used for acquiring a second image of the product to be detected, the second image comprises a second positioning piece, and the second positioning piece is a product component corresponding to the first positioning piece in the second image;
the affine construction module is used for establishing an affine relation between the first image and the second image according to the first positioning piece and the second positioning piece;
the affine module is used for affine matching the area of the first reference piece to the second image according to the affine relation so as to obtain a first to-be-detected area corresponding to the area where the first reference piece is located in the second image;
the image conversion module is used for converting the image of the first region to be detected into a tone gray image and acquiring a first gray value of each pixel point in the tone gray image;
and the analysis processing module is used for judging that the first to-be-detected piece of the to-be-detected product is installed qualified when the total pixel area of the pixel points of which the first gray value is within the preset gray value range is larger than a first threshold value.
6. The product reliability testing device of claim 5, wherein the affine module is specifically configured to establish an affine relationship between the first image and the second image according to the relative position or coordinate of the first positioning element in the first image and the relative position or coordinate of the second positioning element in the second image.
7. The product reliability testing device according to claim 5, wherein the image conversion module comprises:
the first conversion module is used for splitting the image of the first region to be detected into a red gray image, a blue gray image and a green gray image;
and the second conversion module is used for converting the red gray image, the blue gray image and the green gray image into a tone gray image.
8. The product reliability testing device of any of claims 5-7 wherein the first image further comprises a plurality of second reference features having shape characteristics;
the affine module is further configured to affine the region of the second reference piece to the second image according to the affine relation, so as to obtain a second to-be-detected region in the second image, which corresponds to the region where the second reference piece is located;
the analysis processing module is further configured to determine that the second to-be-detected pieces of the to-be-detected product are installed qualified when the number of the second to-be-detected pieces in the second to-be-detected area, which have a shape matching degree with the second reference piece that is greater than or equal to a second threshold value, is equal to the number of the second reference pieces of the first image.
9. A computer-readable storage medium storing computer-executable program code for causing a computer to perform the product reliability test method of any one of claims 1 to 4.
10. An electronic device, comprising:
a processor and a memory electrically connected to the processor, the memory storing program code executable by the processor, the program code when invoked and executed by the processor performing the product reliability testing method of any of claims 1-4.
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| PCT/CN2020/109348 WO2022032675A1 (en) | 2020-08-14 | 2020-08-14 | Product testing method and apparatus, computer readable storage medium, and electronic device |
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| CN117197129A (en) * | 2023-11-03 | 2023-12-08 | 浙江鑫柔科技有限公司 | Blackening degree detection method and device and computer equipment |
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| CN116503386B (en) * | 2023-06-25 | 2023-12-01 | 宁德时代新能源科技股份有限公司 | Method and device for detecting structural adhesive, terminal and computer readable storage medium |
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