TWI830553B - Method for detecting wear of vehicle windows and related devices - Google Patents

Abstract

The present application provides a method for detecting wear of vehicle windows and related devices. The method includes: obtaining an original image of window glass of a vehicle; establishing an image coordinate system based on the original image, obtaining coordinates of each pixel in the original image in the image coordinate system; converting the original image to a gray image; performing an image enhancement on the gray image to obtain an enhanced image; obtaining a first image area whose pixel values are greater than or equal to a first preset value from the enhanced image; based on the first image area, determining a worn area of the window glass. The method can improve the effectiveness of window wear detection.

Description

Vehicle window wear detection methods and related equipment

The present invention relates to the field of image processing technology, and in particular to a vehicle window wear detection method and related equipment.

When a vehicle is driven for a long time, the window glass on the vehicle will be damaged or scratched after being wiped by the wiper and natural wear and tear. If the window glass is worn for a long time, it will affect the recognition of the surrounding environment while driving, thus affecting driving safety. It is common knowledge that vehicle maintenance often focuses on the repair and maintenance of tires and neglects the care of window glass, resulting in the glass having to be replaced after long-term wear and tear, resulting in waste.

In view of the above, it is necessary to provide a vehicle window wear detection method and related equipment that can solve the technical problem of long-term wear and tear of vehicle windows that affects driving safety.

This application provides a vehicle window wear detection method. The method includes: obtaining an original image of the vehicle window glass; establishing an image coordinate system based on the original image, and obtaining the location of each element point in the original image. coordinates in the image coordinate system; perform grayscale processing on the original image to obtain a grayscale image; perform image enhancement on the grayscale image to obtain an enhanced image; from the enhanced image Obtain a first image area with a primitive value greater than or equal to a first preset value; and determine the wear area of the window glass based on the first image area.

In some optional implementations, image enhancement of the grayscale image includes The method includes: calculating the target primitive value of the grayscale image; modifying the primitive value in the grayscale image that is greater than the target primitive value and smaller than the first preset value to the first preset value. Set a value, and modify the primitive value that is smaller than the target primitive value and larger than the second preset value to the second preset value, and the first preset value is larger than the second preset value.

In some optional implementations, calculating the target primitive value of the grayscale image includes: calculating the maximum primitive value corresponding to the primitive point in the grayscale image. According to the maximum primitive value A first preset percentage of the value determines the target primitive value.

In some optional implementations, determining the wear area of the window glass based on the first image area includes: calculating the primitive value of each column of primitive points in the first image area. The accumulated value of A boundary and a second boundary; determining the width of the wear area based on the first boundary and the second boundary, and determining the width of the wear area based on the number of primitive points located on the first center line in the first image area The length of the wear zone.

In some optional implementations, the first center line divides the first image area into a first area and a second area, and the first step of determining the wear area based on the first center line The boundary and the second boundary include: obtaining at least one column of primitive points in the first area whose cumulative primitive value is greater than a second preset percentage of the first centerline cumulative primitive value, and adding the distance between them The farthest column of primitive points of the first center line is used as the first boundary; in the second area, a second preset with a cumulative value of primitive values greater than the cumulative value of the first midline primitive value is obtained. percentage of at least one column of primitive points, and the column of primitive points farthest from the first centerline is used as the second boundary.

In some optional implementations, determining the wear area of the window glass based on the first image area includes: calculating the primitive value of each row of primitive points in the first image area. The accumulated value of Three boundaries and a fourth boundary; determine the width of the wear area according to the third boundary and the fourth boundary, according to the The number of primitive points located in the first image area on the second center line determines the length of the wear area.

In some optional implementations, the second center line divides the first image area into a third area and a fourth area, and the third area of the wear area is determined based on the second center line. The boundary and the fourth boundary include: obtaining at least one column of primitive points in the third area whose cumulative primitive value is greater than a second preset percentage of the second centerline cumulative primitive value, and adding the distance between them The farthest row of primitive points of the second midline is used as the third boundary; in the fourth area, a second preset is obtained in which the cumulative value of primitive values is greater than the cumulative value of the second midline primitive value. percentage of at least one column of primitive points, and the row of primitive points farthest from the second center line is used as the fourth boundary.

In some optional implementations, obtaining a first image region with a primitive value greater than or equal to the first preset value from the enhanced image includes: performing a binary process on the enhanced image. processing to obtain a binarized image; and obtain the first image area from the binarized image.

This application also provides an electronic device. The electronic device includes a processor and a storage. The processor is configured to implement the vehicle window wear detection method when executing a computer program stored in the storage.

The application also provides a computer-readable storage medium. A computer program is stored on the computer-readable storage medium. When the computer program is executed by a processor, the vehicle window wear detection method is implemented.

The vehicle window wear detection method provided by this application obtains the original image of the vehicle window glass; establishes an image coordinate system based on the original image, and obtains the position of each element point in the original image in the image coordinate system coordinates; perform grayscale processing on the original image to obtain a grayscale image; perform image enhancement on the grayscale image to obtain an enhanced image; obtain from the enhanced image a primitive value greater than Or a first image area equal to a first preset value; based on the first image area, the wear area of the window glass is determined. The vehicle window wear detection method provided by this application can improve the effectiveness of vehicle window wear.

1: Electronic equipment

11:Storage

12: Processor

13: Communication bus

S21~S26: Steps

A, B, C, D: points on the image coordinate system

FIG. 1 is a schematic structural diagram of an electronic device provided by an embodiment of the present application.

Figure 2 is a flow chart of a vehicle window wear detection method provided by an embodiment of the present application.

Figure 3 is a schematic diagram of detecting the first center line, the first boundary and the second boundary of the wear area from the first image area.

FIG. 4 is a schematic diagram of detecting the second center line, the third boundary and the fourth boundary of the wear area from the first image area.

To facilitate understanding, some descriptions of concepts related to the embodiments of the present application are exemplarily provided for reference.

It should be noted that "at least one" in this application refers to one or a plurality, and "plural" refers to two or more than two. "And/or" describes the relationship between related objects, indicating that there can be three relationships. For example, A and/or B can mean: A exists alone, A and B exist simultaneously, and B exists alone, where A and B can Be singular or plural. The terms "first", "second", "third", "fourth", etc. (if present) in the description, claim and drawings of this application are used to distinguish similar objects and are not used to refer to them. Used to describe a specific order or sequence.

In order to better understand the vehicle window wear detection method and related equipment provided by the embodiments of the present application, the application scenarios of the vehicle window wear detection method of the present application are first described below.

Figure 1 is a schematic diagram of the application scenario of the vehicle window wear detection method provided by the embodiment of the present application. The vehicle window wear detection method provided by the embodiment of the present application is applied to electronic equipment. Referring to FIG. 1 , the electronic device 1 includes, but is not limited to, a memory 11 and at least one processor 12 . The storage 11 and the processor 12 may be connected through the communication bus 13 or directly connected.

The electronic device 1 may be a computer, a mobile phone, a tablet computer, a personal digital assistant (Personal Digital Assistant, PDA) and other devices. Those skilled in the art can understand that the schematic diagram 1 is only an example of the electronic device 1 and does not constitute a limitation on the electronic device 1. It may include more or fewer components than shown in the figure, or some components may be combined or different. components, for example, the electronic device 1 may also include input and output devices, network access devices, etc.

When a vehicle is driven for a long time, the window glass on the vehicle will be damaged or scratched after being wiped by the wiper and natural wear and tear. If the window glass is worn for a long time, it will affect the recognition of the surrounding environment while driving, thus affecting driving safety. It is common knowledge that vehicle maintenance often focuses on the repair and maintenance of tires and neglects the care of window glass, resulting in the glass having to be replaced after long-term wear and tear, resulting in waste.

In order to solve the above technical problems, embodiments of the present application provide a vehicle window wear detection method. Figure 2 is a flow chart of a vehicle window wear detection method provided by an embodiment of the present application. The vehicle window wear detection method is applied in electronic equipment. Depending on different needs, the order of steps in this flowchart can be changed and some steps can be omitted.

Step S21 is to obtain the original image of the vehicle window glass.

The window wear detection method provided by the embodiment of the present application can be used to detect the wear area of the front window glass, rear window glass or side window glass of the vehicle. Correspondingly, the electronic device acquires the original image of the vehicle's front window glass, rear window glass or side window glass, and the electronic device may be a device with a camera function.

Taking the front window glass as an example, a shield that can completely block the front window glass is placed outside the front window glass. The shield includes but is not limited to white paper. A device with a camera function is used on the inside of the front window glass to capture the front window glass, and the captured image is used as the original image of the car window glass. Among them, the inner side of the front window glass is the side located inside the vehicle, and the outer side of the front window glass is the side located on the outer surface of the vehicle.

Since the area of the front window glass is relatively large, the original image taken can be divided into multiple original images for processing respectively, and each divided original image is labeled, so that when combining all labeled original images, The actual shooting area of the front window glass can be restored.

Step S22 is to establish an image coordinate system based on the original image, and obtain the coordinates of each primitive point in the original image in the image coordinate system.

The electronic device establishes an image coordinate system for the original image based on the original image obtained in step S21. The original image has four vertices. An image coordinate system can be established using any vertex corner of the original image as the origin of the coordinate system, and the position of each primitive point in the original image in the image coordinate system can be obtained. middle coordinates.

In the embodiment of this application, the original image is a color image.

Step S23 is to perform grayscale processing on the original image to obtain a grayscale image.

Grayscale processing is the process of converting a color image into a grayscale image. In a color image, the primitive value of a primitive point includes three components: red (R), green (G), and blue (B). The primitive point displays different colors according to different primitive values. Grayscale It is the process of making the R, G, and B components of the primitive points of the color image equal. During the process of shooting the original image, due to lighting or other influencing factors, there may be colors other than grayscale in the original image. In order to avoid calculation errors, the original image is grayscaled. In a grayscale processed image, the primitive value of each primitive point is a numerical value. The primitive value corresponds to the brightness of the primitive point. The higher the primitive value, the higher the brightness.

Step S24 is to perform image enhancement on the grayscale image to obtain an enhanced image.

After obtaining the grayscale image, since the differences in the areas corresponding to different primitive points are not obvious, the grayscale image is image enhanced to make the light and dark divisions in the grayscale image obvious.

In some embodiments of the present application, the target primitive value of the grayscale image is calculated; the primitive values in the grayscale image that are greater than the target primitive value and smaller than the first preset value are Modify to the first preset value, modify the primitive value that is less than or equal to the target primitive value and greater than the second preset value to the second preset value, and the first preset value is greater than the the second default value.

The calculation of the target primitive value of the grayscale image includes: calculating the maximum primitive value corresponding to the primitive point in the grayscale image, and determining the first preset percentage of the maximum primitive value as The target primitive value. Specifically, the first preset percentage may be 95%, and 95% of the maximum graphic element value is used as the target graphic element value. For example, if the maximum primitive value obtained is 100, the target primitive value is 95.

For example, the grayscale image that undergoes grayscale processing contains lighter areas and darker areas. For the brighter areas, the brightness is increased, and for the darker areas, the darkness is reduced, so that the difference between the brighter areas and the darker areas is Obvious. Assume that the first preset value is 200, the second preset value is 40, the maximum obtained primitive value is 100, and the target primitive value is 95. When the primitive value of the primitive point is identified in the grayscale image is 98 hours, Since the primitive value of 98 is greater than the target primitive value of 95 and smaller than the first preset value of 200, the primitive value of 98 corresponding to the primitive point is modified to 200. When the primitive point is identified in the grayscale image, When the primitive value is 90, since the primitive value of 90 is smaller than the target primitive value of 95 and greater than the second preset value of 40, the primitive value of 90 corresponding to the primitive point is modified to 40 to make the brighter area and the darker area The difference in the area is obvious, and the enhanced image with obvious difference between the brighter area and the darker area is obtained. When it is recognized that the primitive value of a primitive point is less than 40 in the grayscale image, the primitive value less than 40 can be modified to 40, or the current primitive value less than 40 can be retained.

For example, the grayscale image that undergoes grayscale processing contains lighter areas and darker areas. For the brighter areas, the brightness is increased, and for the darker areas, the darkness is reduced, so that the difference between the brighter areas and the darker areas is Obvious. Assume that the first preset value is 200, the second preset value is 40, the maximum obtained primitive value is 220, and the target primitive value is 209. When the primitive value of the primitive point is identified as 210 in the grayscale image, since the primitive value of 210 is greater than the target primitive value of 209 but not smaller than the first preset value of 200, the primitive point corresponding to 210 can be The primitive value is modified to 200, or left at 210. When the primitive value of the primitive point is identified as 205 in the grayscale image, since the primitive value of 205 is smaller than the target primitive value of 209 and larger than the second preset value of 40, the image corresponding to the primitive point of 205 is The element value is modified to 40 to make the difference between the brighter area and the darker area obvious, and obtain an enhanced image with obvious differences between the brighter area and the darker area. When it is recognized that the primitive value of a primitive point is less than 40 in the grayscale image, the primitive value less than 40 can be modified to 40, or the current primitive value less than 40 can be retained.

For example, the grayscale image that undergoes grayscale processing contains lighter areas and darker areas. For the brighter areas, the brightness is increased, and for the darker areas, the darkness is reduced, so that the difference between the brighter areas and the darker areas is Obvious. Assume that the first preset value is 200, the second preset value is 40, the maximum obtained primitive value is 30, and the target primitive value is 29. When the primitive value of the primitive point is identified as 35 in the grayscale image, since the primitive value of 35 is greater than the target primitive value of 29 and smaller than the first preset value of 200, the image corresponding to the primitive point of 35 is The yuan value is modified to 200. When the primitive value of the primitive point is identified as 20 in the grayscale image, since the primitive value of 20 is smaller than the target primitive value of 29 but not greater than the second preset value of 40, the primitive point corresponding to 20 can be Modify the primitive value to 40 or leave it at 20 to make the difference between the brighter area and the darker area obvious, and obtain an enhanced image with obvious differences between the brighter area and the darker area.

Step S25 is to obtain a first image area whose primitive value is greater than or equal to a first preset value from the enhanced image.

In some embodiments of the present application, after obtaining the enhanced image, the enhanced image is binarized to obtain a binary image. The binary image contains two primitive values. Using these two The primitive value divides the binary image into a first image area and a second image area, that is, a brighter area and a darker area. Assuming that the first preset value is 200, the area where the primitive value is greater than or equal to 200 is regarded as the first image area, that is, the brighter area, and the area where the primitive value is less than 200 is regarded as the second image area, that is, Darker areas.

Step S26 is to determine the wear area of the window glass based on the first image area.

Based on the image coordinate system established for the original image, calculate the coordinates of the first image area in the binary image, that is, the coordinates of the brighter area, and determine the coordinates of the first image area based on the coordinates of the first image area. Worn areas of car windows.

FIG. 3 is a schematic diagram of detecting the first center line, the first boundary and the second boundary of the wear area from the first image area.

In some embodiments of the present application, the wear area of the vehicle window glass is determined based on the first image area, that is, the first image area is a brighter area, and the vehicle window is determined based on the brighter area. The wear area of glass includes: calculating the cumulative value of the primitive values of each column of primitive points in the first image area; taking a column of primitive points with the largest cumulative value in the first image area as the a first center line of the first image area; determining a first boundary and a second boundary of the wear area based on the first center line; determining a first boundary and a second boundary of the wear area based on the first boundary and the second boundary Width, the length of the wear area is determined based on the number of primitive points located in the first image area on the first center line.

Exemplarily, calculate the accumulation of primitive values of each column of primitive points in the first image area value, take the column with the maximum accumulated value as the first center line of the first image area, traverse the first image area with the first center line as the starting point, and determine the first boundary and the second boundary of the wear area, according to The first boundary and the second boundary determine the width of the wear boundary, and the length of the wear area is determined according to the number of primitive points on the first center line.

In one embodiment of the present application, the first center line divides the first image area into a first area and a second area, and the first step of determining the wear area based on the first center line The boundary and the second boundary include: obtaining at least one column of primitive points in the first area whose cumulative primitive value is greater than a second preset percentage of the first centerline cumulative primitive value, and adding the distance between them The farthest column of primitive points of the first center line is used as the first boundary; in the second area, a second preset with a cumulative value of primitive values greater than the cumulative value of the first midline primitive value is obtained. percentage of at least one column of primitive points, and the column of primitive points farthest from the first centerline is used as the second boundary.

For example, in the binary image, there will be many points in the brighter area. The brighter area described in this application is an area larger than the preset range. The brighter area formed by smaller points can be ignored. .

The first center line is a line parallel to the Y-axis, dividing the first image area into a first area and a second area. For the first area, based on the primitive value of each column of the first image area, obtain at least one column of primitive points whose accumulated value of the primitive value is greater than a second preset percentage of the accumulated value of the first centerline primitive value, and The column of primitive points farthest from the first centerline is used as the first boundary, wherein the second preset percentage may be 80%, assuming that the accumulated value (maximum accumulated value) of the first centerline primitive value is 90, Then, obtain at least one column of primitive points whose cumulative primitive value is greater than the second preset percentage of the first centerline primitive value cumulative value, which may include 76,...,80, etc. Therefore, the first boundary may be a primitive The column where the cumulative value of the value is 76 is located. Similarly, for the second area, the column where the cumulative value of the primitive is 76 is used as the second boundary. As shown in Figure 3, obtain the primitive points at both ends of the column with the maximum cumulative value (for example, the primitive cumulative value is 90), set them as point A and point B respectively, and pass through point A, point B and X axis parallel straight line Intersect with the first boundary and the second boundary respectively to construct a rectangular area as the wear area. The distance between the first boundary and the second boundary is the width value of the wear area, and the number of primitive points on the first center line is the length value of the wear area.

FIG. 4 is a schematic diagram of detecting the second center line, the third boundary and the fourth boundary of the wear area from the first image area.

In one embodiment of the present application, determining the wear area of the window glass based on the first image area includes: calculating the primitive value of each row of primitive points in the first image area. The accumulated value of Three boundaries and a fourth boundary; determining the width of the wear area based on the third boundary and the fourth boundary, and determining the width of the wear area based on the number of primitive points located in the first image area on the second center line The length of the wear zone.

Exemplarily, calculate the accumulated value of the primitive values of each row of primitive points in the first image area, and use the row with the maximum accumulated value as the second center line of the first image area, and use the second center line Traverse the first image area as the starting point, determine the third boundary and the fourth boundary of the wear area, determine the width of the wear boundary based on the third boundary and the fourth boundary, and determine the wear area based on the number of primitive points on the second center line length.

In one embodiment of the present application, the second center line divides the first image area into a third area and a fourth area, and the third step of determining the wear area based on the second center line The boundary and the fourth boundary include: obtaining at least one column of primitive points in the third area whose cumulative primitive value is greater than a second preset percentage of the second centerline cumulative primitive value, and adding the distance between them The farthest row of primitive points of the second midline is used as the third boundary; the cumulative value of primitive values obtained in the fourth area is greater than the cumulative cumulative value of primitive values of the second midline At least one column of primitive points with a second preset percentage of the value, and a row of primitive points farthest from the second center line is used as the fourth boundary.

For example, in the binary image, there will be many points in the brighter area. The brighter area described in this application is an area larger than the preset range. The brighter area formed by smaller points can be ignored. .

The second center line is a line parallel to the X-axis, dividing the first image area into a third area and a fourth area. For the third area, based on the above-mentioned acquisition of the primitive values of each row of the first image area, obtain at least one column of primitives whose cumulative value of primitive values is greater than a second preset percentage of the second center line cumulative value of primitive values. points, and the column of primitive points farthest from the second midline is used as the third boundary, where the second preset percentage may be 80%, assuming that the cumulative value of the second midline primitive value (maximum cumulative value) is 90, then, obtain at least one column of primitive points whose cumulative value of primitive values is greater than the second preset percentage of the second center line cumulative value of primitive values, which may include, 76,...,80, etc., therefore, the third boundary can is the column where the accumulated value of the primitive value is 76. Similarly, for the fourth area, the row where the accumulated value of the primitive value is 76 is used as the fourth boundary. As shown in Figure 4, obtain the primitive points at both ends of the row with the maximum accumulated value (for example, the accumulated value of the primitive is 90), and set them as point C and point D respectively, and according to passing through point C and point D and with The straight lines parallel to the Y-axis intersect the first boundary and the second boundary respectively, forming a rectangular area as the wear area. The distance between the third boundary and the fourth boundary is the width value of the wear area. The primitive point on the second center line Quantity as length value of the wear area.

In one embodiment of the present application, the position of the wear area on the front window glass is determined based on the position of the wear area in the image coordinate system.

Multiple labeled original images are combined into the size shown on the front window glass. According to the image coordinate system established in each original image, the wear area in the coordinate system can be calculated. According to the wear area in the image The position of the coordinate system can be used to determine the actual position of the front window where the wear area is located.

This application uses grayscale processing and image enhancement processing on the original image to make the differences in the areas where different picture element points are obvious. The image after image processing is binarized. On the basis of image enhancement, the binarized partitions are obvious. By judging the primitive values, the first image with the wear area is determined. image area, which improves the detection effect of the window wear area. When the window wear is not obvious, image enhancement and binary processing can greatly improve the effectiveness of retrieval and avoid irreversible wear caused by long-term wear, so that maintenance personnel can promptly maintain the worn area.

Please continue to refer to FIG. 1 . In this embodiment, the memory 11 may be an internal memory of the electronic device 1 , that is, a memory built into the electronic device 1 . In other embodiments, the storage 11 may also be an external storage of the electronic device 1 , that is, a storage external to the electronic device 1 .

In some embodiments, the storage 11 is used to store program codes and various data, and realize high-speed and automatic access to programs or data during the operation of the electronic device 1 .

The storage 11 may include random access memory, and may also include non-volatile storage, such as hard disk, memory, plug-in hard disk, smart memory card (Smart Media Card, SMC), Secure Digital (SD) card, memory card (Flash Card), at least one disk storage device, flash memory device, or other volatile solid-state storage device.

In one embodiment, the processor 12 may be a central processing unit (Central Processing Unit, CPU), or other general-purpose processor, digital signal processor (Digital Signal Processor, DSP), special application integrated circuit ( Application Specific Integrated Circuit (ASIC), Field-Programmable Gate Array (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general processor may be a microprocessor or the processor may be any other conventional processor.

If the program codes and various data in the storage 11 are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the present application implements all or part of the processes in the above embodiment methods, such as the car window wear detection method, which can also be completed by instructing relevant hardware through a computer program. The computer program can be stored in the computer. In a readable storage medium, when the computer program is executed by the processor, the steps of each of the above method embodiments can be implemented. Wherein, the computer program includes computer program code, and the computer program code can be in the form of original program code, object code form, executable file or some intermediate form, etc. The computer-readable medium may include: any entity or device capable of carrying the computer program code, Recording media, pen drives, mobile hard drives, magnetic disks, optical disks, computer storage, read-only memory (ROM, Read-Only Memory), etc.

It can be understood that the module division described above is a logical function division, and there may be other division methods in actual implementation. In addition, each functional module in each embodiment of the present application can be integrated in the same processing unit, or each module can physically exist separately, or two or more modules can be integrated in the same unit. The above integrated modules can be implemented in the form of hardware or in the form of hardware plus software function modules.

Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application and are not limiting. Although the present application has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical solutions of the present application can be modified. Modifications or equivalent substitutions may be made without departing from the spirit and scope of the technical solution of the present application.

S21~S26: Steps

Claims (9)

A vehicle window wear detection method, applied to electronic equipment, wherein the method includes: obtaining an original image of the vehicle window glass; establishing an image coordinate system based on the original image, and obtaining each primitive in the original image the coordinates of the point in the image coordinate system; performing grayscale processing on the original image to obtain a grayscale image, including calculating the target primitive value of the grayscale image; converting the grayscale image into The primitive values in the image that are greater than the target primitive value and smaller than the first preset value are modified to the first preset value, and the primitive values that are smaller than the target primitive value and greater than the second preset value are modified. The value is modified to the second preset value, and the first preset value is greater than the second preset value; image enhancement is performed on the grayscale image to obtain an enhanced image; from the enhanced image Obtain a first image area with a primitive value greater than or equal to a first preset value; based on the first image area, determine the wear area of the window glass, including calculating a binary value according to the image coordinate system The coordinates of the first image area in the image are determined, and the wear area of the window glass is determined based on the coordinates of the first image area. The vehicle window wear detection method according to claim 1, wherein calculating the target primitive value of the grayscale image includes: calculating the maximum primitive value corresponding to the primitive point in the grayscale image, The target primitive value is determined according to a first preset percentage of the maximum primitive value. The vehicle window wear detection method according to claim 1, wherein determining the wear area of the vehicle window glass based on the first image area includes: calculating each column diagram in the first image area The accumulated value of the primitive value of the primitive point; taking a column of primitive points with the maximum cumulative value in the first image area as the first center line of the first image area; determining based on the first center line The first boundary and the second boundary of the wear area; the width of the wear area is determined according to the first boundary and the second boundary, and the width of the wear area is determined according to the first center line located in the first image area. The number of primitive points determines the length of the wear area. The vehicle window wear detection method according to claim 3, wherein the first center line divides the first image area into a first area and a second area, and the determination based on the first center line The first boundary and the second boundary of the wear area include: obtaining at least one column of primitives in the first area whose cumulative primitive value is greater than a second preset percentage of the first centerline cumulative primitive value. points, and the column of primitive points farthest from the first centerline is used as the first boundary; the cumulative value of the primitive values obtained in the second area is greater than the cumulative cumulative value of the first midline primitive values. At least one column of primitive points that is the second preset percentage of the value, and the column of primitive points that is farthest from the first centerline is used as the second boundary. The vehicle window wear detection method according to claim 1, wherein determining the wear area of the vehicle window glass based on the first image area includes: calculating each row of images in the first image area The accumulated value of the primitive value of the primitive point; taking a row of primitive points with the maximum cumulative value in the first image area as the second center line of the first image area; determining based on the second center line The third boundary and the fourth boundary of the wear area; the width of the wear area is determined according to the third boundary and the fourth boundary, and the width of the wear area is determined according to the second center line located in the first image area. The number of primitive points determines the length of the wear area. The vehicle window wear detection method according to claim 5, wherein the second center line divides the first image area into a third area and a fourth area, and the determination based on the second center line The third boundary and the fourth boundary of the wear area include: obtaining at least one column of primitives in the third area whose cumulative primitive value is greater than a second preset percentage of the second centerline cumulative primitive value. points, and the row of primitive points farthest from the second midline is used as the third boundary; the cumulative value of primitive values obtained in the fourth area is greater than the cumulative cumulative value of primitive values of the second midline At least one column of primitive points with a second preset percentage of the value, and a row of primitive points farthest from the second center line is used as the fourth boundary. The vehicle window wear detection method according to claim 1, wherein said obtaining a first image area with a primitive value greater than or equal to the first preset value from the enhanced image includes: The enhanced image is binarized to obtain a binarized image; and the first image area is obtained from the binarized image. An electronic device, wherein the electronic device includes a processor and a storage, and the processor is used to execute a computer program stored in the storage to implement the vehicle window wear detection method as described in any one of claims 1 to 7 . A computer-readable storage medium, wherein the computer-readable storage medium stores at least one instruction. When the at least one instruction is executed by a processor, the vehicle window wear detection as described in any one of claims 1 to 7 is implemented. method.

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