CN111899238A - Defect detection method, device, medium and electronic equipment for double-light source image - Google Patents
Defect detection method, device, medium and electronic equipment for double-light source image Download PDFInfo
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- WHXSMMKQMYFTQS-UHFFFAOYSA-N Lithium Chemical compound [Li] WHXSMMKQMYFTQS-UHFFFAOYSA-N 0.000 claims description 11
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Abstract
The embodiment of the application discloses a method, a device, a medium and electronic equipment for detecting defects of a double-light source image. The method comprises the following steps: acquiring a stroboscopic double-light source image of an object to be detected; the pixel points of the stroboscopic double-light source image are staggered line by a first light source and a second light source; splitting the stroboscopic double-light source image according to a light source to obtain a first light source image and a second light source image; determining the gray average value of pixel points in the first light source image and the second light source image and a preset gray threshold value, and performing binarization processing on the images; determining abnormal points of the first light source image and the second light source image according to a binarization processing result; and determining the defect type of the abnormal point according to the pixel attributes of the abnormal point in the first light source image and the second light source image. By executing the scheme, the purpose of accurately identifying the defects in the image can be achieved through the image shot under the stroboscopic double-light-source condition.
Description
Technical Field
The embodiment of the application relates to the technical field of image processing, in particular to a method, a device, a medium and electronic equipment for detecting defects of a double-light source image.
Background
With the rapid development of science and technology, the application of detecting articles through the images of the articles is more and more extensive. Taking a lithium battery diaphragm as an example, in order to detect oil spots, broken holes and other defects in the lithium battery diaphragm, after an image of the lithium battery diaphragm is obtained, the image is often identified, and whether an abnormal point or an abnormal area exists in the image is determined. However, the identification mode is single, and for various types of defects, the defects cannot be accurately identified and the defect types cannot be divided, so that secondary manual inspection is required, and the efficiency and the accuracy are difficult to control.
Disclosure of Invention
The embodiment of the application provides a method, a device, a medium and electronic equipment for detecting defects of a double-light source image, which can achieve the purpose of accurately identifying the defects in the image through the image shot under a stroboscopic double-light source.
In a first aspect, an embodiment of the present application provides a method for detecting defects in a dual-light source image, where the method includes:
acquiring a stroboscopic double-light source image of an object to be detected; the pixel points of the stroboscopic double-light source image are staggered line by a first light source and a second light source;
splitting the stroboscopic double-light source image according to a light source to obtain a first light source image and a second light source image;
determining the gray average value of pixel points in the first light source image and the second light source image and a preset gray threshold value, and performing binarization processing on the images;
determining abnormal points of the first light source image and the second light source image according to a binarization processing result;
and determining the defect type of the abnormal point according to the pixel attributes of the abnormal point in the first light source image and the second light source image.
Further, the object to be tested includes: a lithium battery separator.
Further, splitting the stroboscopic double-light source image according to a light source to obtain a first light source image and a second light source image, including:
determining first light source pixel point rows in the stroboscopic double-light source image, and splicing all the first light source pixel point rows according to a set sequence to obtain a first light source image;
and the number of the first and second groups,
and determining second light source pixel point rows in the stroboscopic double-light source image, and splicing all the second light source pixel point rows according to a set sequence to obtain a second light source image.
Further, after determining the outliers of the first and second illuminant images, the method further comprises:
taking the abnormal points as defect counting points, and determining the pixel attributes of a defect area formed by the defect counting points;
correspondingly, determining the defect type of the outlier according to the pixel attributes of the outlier in the first light source image and the second light source image includes:
comparing pixel attributes in the first light source image and the second light source image, and if the pixel attributes meet preset conditions, determining the defect type of the defect area.
Further, the pixel attribute includes at least one of a pixel gray value mean, a pixel gray value variance, and a pixel region area.
Further, the defect types comprise a hole breaking defect, a black point defect, an oil spot defect and a white point defect.
In a second aspect, the present application provides a defect detection apparatus for a dual-light source image, the apparatus including:
the stroboscopic double-light source image acquisition module is used for acquiring a stroboscopic double-light source image of the object to be detected; the pixel points of the stroboscopic double-light source image are staggered line by a first light source and a second light source;
the splitting module is used for splitting the stroboscopic double-light source image according to a light source to obtain a first light source image and a second light source image;
the binarization processing module is used for determining the gray average value of pixel points in the first light source image and the second light source image and a preset gray threshold value, and performing binarization processing on the images;
the abnormal point determining module is used for determining the abnormal points of the first light source image and the second light source image according to the binarization processing result;
and the defect type determining module is used for determining the defect type of the abnormal point according to the pixel attributes of the abnormal point in the first light source image and the second light source image.
Further, the object to be tested includes: a lithium battery separator.
In a third aspect, the present application provides a computer-readable storage medium, on which a computer program is stored, which when executed by a processor, implements the method for detecting defects in a dual-light source image according to the present application.
In a fourth aspect, the present application provides an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor, where the processor executes the computer program to implement the method for detecting defects in a dual-light source image according to the embodiments of the present application.
According to the technical scheme provided by the embodiment of the application, a stroboscopic double-light source image of an object to be detected is obtained; the pixel points of the stroboscopic double-light source image are staggered line by a first light source and a second light source; splitting the stroboscopic double-light source image according to a light source to obtain a first light source image and a second light source image; determining the gray average value of pixel points in the first light source image and the second light source image and a preset gray threshold value, and performing binarization processing on the images; determining abnormal points of the first light source image and the second light source image according to a binarization processing result; and determining the defect type of the abnormal point according to the pixel attributes of the abnormal point in the first light source image and the second light source image. Through adopting the technical scheme that this application provided, can reach the purpose of carrying out accurate discernment to the defect in the image through the image of shooing under the two light sources of stroboscopic.
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FIG. 1 is a flow chart of a method for defect detection of a dual-light source image provided by an embodiment of the present application;
FIG. 2 is a schematic diagram of a strobed dual light source image provided by an embodiment of the present application;
FIG. 3 is a schematic illustration of a split of a stroboscopic dual light source image provided by an embodiment of the present application;
FIG. 4 is a schematic structural diagram of a defect detection apparatus using dual-light source image 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
The present application will be described in further detail with reference to the following drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the application and are not limiting of the application. It should be further noted that, for the convenience of description, only some of the structures related to the present application are shown in the drawings, not all of the structures.
Before discussing exemplary embodiments in more detail, it should be noted that some exemplary embodiments are described as processes or methods depicted as flowcharts. Although a flowchart may describe the steps as a sequential process, many of the steps can be performed in parallel, concurrently or simultaneously. In addition, the order of the steps may be rearranged. The process may be terminated when its operations are completed, but may have additional steps not included in the figure. The processes may correspond to methods, functions, procedures, subroutines, and the like.
Fig. 1 is a flowchart of a defect detection method using a dual-light source image according to an embodiment of the present application, where the present embodiment is applicable to a defect detection situation of a lithium battery diaphragm, and the method can be executed by a defect detection apparatus using a dual-light source image according to an embodiment of the present application, and the apparatus can be implemented by software and/or hardware, and can be integrated in an electronic device having a corresponding operation capability.
As shown in fig. 1, the method for detecting defects in a dual-light source image includes:
s110, acquiring a stroboscopic double-light source image of an object to be detected; the pixel points of the stroboscopic double-light source image are staggered line by the first light source and the second light source.
The strobing double-light source image can be an image obtained under the strobing condition of the double-light source. The double light source can be a white light source, combined with other light sources, or combined with any two other light sources. Specifically, the pixel points of the stroboscopic dual-light-source image may be formed by staggering a first light source scanning line and a second light source scanning line.
Figure 2 is a schematic diagram of a strobed dual light source image provided by an embodiment of the present application. As shown in fig. 2, for example, the image has 720 rows of pixel points, where the pixel points in the odd rows such as the first row, the third row, the fifth row, etc. may be the first light source scanning row, and the pixel points in the even rows such as the second row, the fourth row, the sixth row, etc. may be the second light source scanning row. It can be understood that, since the height occupied by each pixel point row in the image is very small, the range characteristics that can be represented on two adjacent pixel point rows are close to each other if there is a defect for the object to be measured. Thus, a strobed dual light source image can be split into two images according to the light source.
And S120, splitting the stroboscopic double-light source image according to a light source to obtain a first light source image and a second light source image.
The splitting is performed according to the light source, and the splitting can be performed according to the color of the light source. In other embodiments, the distinction may also be made according to the angle, orientation, and other physical information of the light source. Because the stroboscopic double-light-source image is obtained by adopting two light sources, the stroboscopic double-light-source image can be distinguished according to the two light sources. And another attribute of the strobed dual light source image is that the source scan lines overlap so that the same defect can be displayed in both images after splitting.
In this embodiment, optionally, splitting the stroboscopic dual-light source image according to a light source to obtain a first light source image and a second light source image, including:
determining first light source pixel point rows in the stroboscopic double-light source image, and splicing all the first light source pixel point rows according to a set sequence to obtain a first light source image;
and the number of the first and second groups,
and determining second light source pixel point rows in the stroboscopic double-light source image, and splicing all the second light source pixel point rows according to a set sequence to obtain a second light source image.
Fig. 3 is a schematic illustration of a split of a stroboscopic dual light source image provided by an embodiment of the present application. As shown in fig. 3, in the stroboscopic dual-light source image, after the first light source scan line and the second light source scan line are split, the first light image and the second light image are sequentially spliced according to the light sources. Specifically, the stitching can be performed according to the line number of each pixel point line in the original stroboscopic dual-light source image. Therefore, two images with the height being half of that of the original stroboscopic double-light source image can be obtained, and the two images can be displayed aiming at the defects of the object to be detected. According to the technical scheme, by means of the arrangement, abnormal points in the stroboscopic double-light source image can be reserved, and differential display can be performed on the pixel points in the abnormal range through different light source images, so that the types of the abnormal images are further distinguished.
S130, determining a gray average value of pixel points in the first light source image and the second light source image and a preset gray threshold value, and performing binarization processing on the images.
After the first light source image and the second light source image are obtained, the gray level images of the first light source image and the second light source image can be determined. That is, the pixel value of each pixel point is converted into a gray value. After the gray level image is obtained, a gray level threshold value can be determined according to the average value of the gray levels of the pixel points of the first light source image, and binarization processing is performed on the first light source image according to the gray level threshold value. Besides, binarization processing can be carried out on the image according to the average value of the gray levels of the pixel points and a preset gray threshold value. Accordingly, a similar processing may be applied to the second source image.
It can be understood that, in the process of performing binarization processing on the two light source images, the preset grayscale threshold may be the same or different. The above scheme may specifically include two cases, and the first light source image is taken as an example to perform a detailed description.
If the mean value of the gray levels of the pixel points in the first light source image is 96, the gray threshold value can be determined to be 100 according to the mean value of the gray levels of the pixel points, and 100 is used as a boundary value of the binarization processing.
The other scheme is as follows: if the average value of the gray levels of the pixel points in the first light source image is 96 and the preset gray threshold value may be 128, the boundary value of the binarization process may be determined according to the size of the difference value between the average value of the gray levels of the pixel points and the preset gray threshold value, for example, 2 times the difference value between 128 and 96 is used as the boundary value.
In this scheme, the result of the binarization processing is that the gray value of the pixel point in the image is either 0 or 255, specifically, 255 may be taken when the gray value is greater than the boundary value, and 0 may be taken when the gray value is less than the boundary value.
And S140, determining abnormal points of the first light source image and the second light source image according to the binarization processing result.
In the scheme, the abnormal pixel points in the first light source image and the abnormal pixel points in the second light source image can be determined according to the binary image obtained by the binary processing. Specifically, the pixel points can be regarded as outliers when black pixel point regions exist in the white background, or the pixel points can be regarded as outliers when white pixel point regions exist in the black background.
S150, determining the defect type of the abnormal point according to the pixel attributes of the abnormal point in the first light source image and the second light source image.
It is understood that due to different light sources and different binarization manners, a part of abnormal points may be abnormal in one light source image but not abnormal in another light source image. Therefore, the defect type of the outlier may be determined according to the pixel properties of the outlier in the first and second light source images after the outlier is determined.
The pixel attributes of the abnormal pixel points may include shapes and areas formed by the abnormal pixel points, mean values of gray values of the abnormal pixel points, variance of gray values of the abnormal pixel points, and the like. In the scheme, the abnormal pixel point is further analyzed according to the determination of the pixel attribute of the abnormal pixel point, and the analysis of the detected object is facilitated.
According to the technical scheme provided by the embodiment of the application, a stroboscopic double-light source image of an object to be detected is obtained; the pixel points of the stroboscopic double-light source image are staggered line by a first light source and a second light source; splitting the stroboscopic double-light source image according to a light source to obtain a first light source image and a second light source image; determining the gray average value of pixel points in the first light source image and the second light source image and a preset gray threshold value, and performing binarization processing on the images; determining abnormal points of the first light source image and the second light source image according to a binarization processing result; and determining the defect type of the abnormal point according to the pixel attributes of the abnormal point in the first light source image and the second light source image. Through adopting the technical scheme that this application provided, can reach the purpose of carrying out accurate discernment to the defect in the image through the image of shooing under the two light sources of stroboscopic.
On the basis of the foregoing technical solution, optionally, after determining the abnormal point of the first light source image and the second light source image, the method further includes:
taking the abnormal points as defect counting points, and determining the pixel attributes of a defect area formed by the defect counting points;
correspondingly, determining the defect type of the outlier according to the pixel attributes of the outlier in the first light source image and the second light source image includes:
comparing pixel attributes in the first light source image and the second light source image, and if the pixel attributes meet preset conditions, determining the defect type of the defect area.
Taking the abnormal points as defect counting points, and determining the pixel attributes of a defect area formed by the defect counting points; comparing pixel attributes in the first light source image and the second light source image, and if the pixel attributes meet preset conditions, determining the defect type of the defect area. Here, the pixel attribute may be a pixel attribute in the first light source image and the second light source image, instead of a pixel attribute in the grayed-out and binarized image. For example, values of three channels of red, green and blue may be included.
After determining the pixel attributes, a defect type of the defect region may be determined based on a difference of the pixel attributes in the first light source image and in the second light source image. For example, a hole is a highlight defect in the image of the first light source and a dark defect in the image of the second light source; the black spot is a dark defect in both figures, the oil spot is highlighted in the image of the first light source, grayed out in the image of the second light source, the white spot is white in both images, and so on.
This technical scheme is through such setting, can better definite defect type, helps carrying out more comprehensive detection to the article that awaits measuring.
On the basis of the above technical solution, optionally, the pixel attribute includes at least one of a pixel gray value mean, a pixel gray value variance, and a pixel region area. In the scheme, the salient features for various types of defects can be obtained by processing and identifying a plurality of samples for the various types of defects, and the features are combined to obtain a feature set, such as a pixel gray value mean, a pixel gray value variance, a pixel region area and the like. Through the arrangement, the defect type can be determined quickly and accurately, and the purpose of dividing the defect type more finely is achieved.
In this embodiment, the defect types may optionally include a hole defect, a black spot defect, an oil spot defect, and a white spot defect. The defects can be regarded as common defect types of lithium battery diaphragms and other battery diaphragms, and specific identification is carried out on the defects of the types, so that the quality of the lithium battery diaphragm and problems existing in the production process can be clearly identified.
Fig. 4 is a schematic structural diagram of a defect detection apparatus using a dual-light source image according to an embodiment of the present application. As shown in fig. 4, the apparatus for detecting defects in a dual light source image includes:
a stroboscopic double-light-source image acquisition module 410, configured to acquire a stroboscopic double-light-source image of an object to be detected; the pixel points of the stroboscopic double-light source image are staggered line by a first light source and a second light source;
the splitting module 420 is configured to split the stroboscopic dual-light source image according to a light source to obtain a first light source image and a second light source image;
a binarization processing module 430, configured to determine a mean value of gray levels of pixel points in the first light source image and the second light source image, and a preset gray threshold, and perform binarization processing on the images;
an abnormal point determining module 440, configured to determine an abnormal point of the first light source image and the second light source image according to a binarization processing result;
a defect type determining module 450, configured to determine a defect type of the outlier according to pixel attributes of the outlier in the first light source image and the second light source image.
Optionally, the object to be tested includes: a lithium battery separator.
The product can execute the method provided by the embodiment of the application, and has the corresponding functional modules and beneficial effects of the execution method.
Embodiments of the present application also provide a storage medium containing computer-executable instructions that, when executed by a computer processor, perform a method of defect detection of a dual light source image, the method comprising:
acquiring a stroboscopic double-light source image of an object to be detected; the pixel points of the stroboscopic double-light source image are staggered line by a first light source and a second light source;
splitting the stroboscopic double-light source image according to a light source to obtain a first light source image and a second light source image;
determining the gray average value of pixel points in the first light source image and the second light source image and a preset gray threshold value, and performing binarization processing on the images;
determining abnormal points of the first light source image and the second light source image according to a binarization processing result;
and determining the defect type of the abnormal point according to the pixel attributes of the abnormal point in the first light source image and the second light source image.
Storage medium-any of various types of memory devices or storage devices. The term "storage medium" is intended to include: mounting media such as CD-ROM, floppy disk, or tape devices; computer system memory or random access memory such as DRAM, DDR RAM, SRAM, EDO RAM, Lanbas (Rambus) RAM, etc.; non-volatile memory such as flash memory, magnetic media (e.g., hard disk or optical storage); registers or other similar types of memory elements, etc. The storage medium may also include other types of memory or combinations thereof. In addition, the storage medium may be located in the computer system in which the program is executed, or may be located in a different second computer system connected to the computer system through a network (such as the internet). The second computer system may provide the program instructions to the computer for execution. The term "storage medium" may include two or more storage media that may reside in different locations, such as in different computer systems that are connected by a network. The storage medium may store program instructions (e.g., embodied as a computer program) that are executable by one or more processors.
Of course, the storage medium provided by the embodiments of the present application contains computer executable instructions, and the computer executable instructions are not limited to the defect detection operation of the dual-light source image as described above, and may also perform related operations in the defect detection method of the dual-light source image as provided by any embodiments of the present application.
The embodiment of the application provides electronic equipment, and the defect detection device of the double-light source image provided by the embodiment of the application can be integrated in the electronic equipment. Fig. 5 is a schematic structural diagram of an electronic device according to an embodiment of the present application. As shown in fig. 5, the present embodiment provides an electronic device 500, which includes: one or more processors 520; the storage device 510 is used for storing one or more programs, when the one or more programs are executed by the one or more processors 520, the one or more processors 520 implement the method for detecting defects in a dual-light source image provided by the embodiment of the present application, the method includes:
acquiring a stroboscopic double-light source image of an object to be detected; the pixel points of the stroboscopic double-light source image are staggered line by a first light source and a second light source;
splitting the stroboscopic double-light source image according to a light source to obtain a first light source image and a second light source image;
determining the gray average value of pixel points in the first light source image and the second light source image and a preset gray threshold value, and performing binarization processing on the images;
determining abnormal points of the first light source image and the second light source image according to a binarization processing result;
and determining the defect type of the abnormal point according to the pixel attributes of the abnormal point in the first light source image and the second light source image.
Of course, those skilled in the art will appreciate that the processor 520 may also implement the solution of the method for detecting defects in a dual-light source image provided in any of the embodiments of the present application.
The electronic device 500 shown in fig. 5 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present application.
As shown in fig. 5, the electronic device 500 includes a processor 520, a storage 510, an input 530, and an output 540; the number of the processors 520 in the electronic device may be one or more, and one processor 520 is taken as an example in fig. 5; the processor 520, the storage 510, the input device 530, and the output device 540 in the electronic apparatus may be connected by a bus or other means, and are exemplified by a bus 550 in fig. 5.
The storage device 510 is a computer readable storage medium, and can be used to store software programs, computer executable programs, and module units, such as program instructions corresponding to the defect detection method of the dual light source image in the embodiment of the present application.
The storage device 510 may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function; the storage data area may store data created according to the use of the terminal, and the like. Further, the storage 510 may include high speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other non-volatile solid state storage device. In some examples, storage 510 may further include memory located remotely from processor 520, which may be connected via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The input means 530 may be used to receive input numbers, character information, or voice information, and to generate key signal inputs related to user settings and function control of the apparatus. The output device 540 may include a display screen, speakers, etc.
The electronic equipment provided by the embodiment of the application can achieve the purpose of accurately identifying the defects in the image through the image shot under the stroboscopic double-light-source condition.
The defect detection device, the medium and the electronic device for the double-light-source image provided in the above embodiments can execute the defect detection method for the double-light-source image provided in any embodiment of the present application, and have corresponding functional modules and beneficial effects for executing the method. For technical details not described in detail in the above embodiments, reference may be made to the method for detecting defects in a dual-light source image provided in any of the embodiments of the present application.
It is to be noted that the foregoing is only illustrative of the preferred embodiments of the present application and the technical principles employed. It will be understood by those skilled in the art that the present application is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the application. Therefore, although the present application has been described in more detail with reference to the above embodiments, the present application is not limited to the above embodiments, and may include other equivalent embodiments without departing from the spirit of the present application, and the scope of the present application is determined by the scope of the appended claims.
Claims (10)
1. A method for detecting defects in a dual-light source image, the method comprising:
acquiring a stroboscopic double-light source image of an object to be detected; the pixel points of the stroboscopic double-light source image are staggered line by a first light source and a second light source;
splitting the stroboscopic double-light source image according to a light source to obtain a first light source image and a second light source image;
determining the gray average value of pixel points in the first light source image and the second light source image and a preset gray threshold value, and performing binarization processing on the images;
determining abnormal points of the first light source image and the second light source image according to a binarization processing result;
and determining the defect type of the abnormal point according to the pixel attributes of the abnormal point in the first light source image and the second light source image.
2. The method of claim 1, wherein the item under test comprises: a lithium battery separator.
3. The method of claim 1, wherein splitting the strobed dual light source image according to light source to obtain a first light source image and a second light source image comprises:
determining first light source pixel point rows in the stroboscopic double-light source image, and splicing all the first light source pixel point rows according to a set sequence to obtain a first light source image;
and the number of the first and second groups,
and determining second light source pixel point rows in the stroboscopic double-light source image, and splicing all the second light source pixel point rows according to a set sequence to obtain a second light source image.
4. The method of claim 1, wherein after determining outliers of the first and second light source images, the method further comprises:
taking the abnormal points as defect counting points, and determining the pixel attributes of a defect area formed by the defect counting points;
correspondingly, determining the defect type of the outlier according to the pixel attributes of the outlier in the first light source image and the second light source image includes:
comparing pixel attributes in the first light source image and the second light source image, and if the pixel attributes meet preset conditions, determining the defect type of the defect area.
5. The method of claim 4, wherein the pixel attributes comprise at least one of a pixel gray value mean, a pixel gray value variance, and a pixel region area.
6. The method of claim 4, wherein the defect types include a hole break defect, a black spot defect, an oil spot defect, and a white spot defect.
7. A dual light source image defect detection apparatus, comprising:
the stroboscopic double-light source image acquisition module is used for acquiring a stroboscopic double-light source image of the object to be detected; the pixel points of the stroboscopic double-light source image are staggered line by a first light source and a second light source;
the splitting module is used for splitting the stroboscopic double-light source image according to a light source to obtain a first light source image and a second light source image;
the binarization processing module is used for determining the gray average value of pixel points in the first light source image and the second light source image and a preset gray threshold value, and performing binarization processing on the images;
the abnormal point determining module is used for determining the abnormal points of the first light source image and the second light source image according to the binarization processing result;
and the defect type determining module is used for determining the defect type of the abnormal point according to the pixel attributes of the abnormal point in the first light source image and the second light source image.
8. The apparatus of claim 7, wherein the item under test comprises: a lithium battery separator.
9. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the method for defect detection of a dual light source image as claimed in any one of claims 1 to 6.
10. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor when executing the computer program implements the method for defect detection of a dual light source image as claimed in any one of claims 1 to 6.
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