CN115311288A - Method for detecting damage of automobile film - Google Patents
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Abstract
The invention relates to the field of automobile film damage detection, and provides an automobile film damage detection method, which comprises the following steps: obtaining a preprocessed RGB image; extracting a dark channel image; obtaining an RGB image of the corresponding minimum sub-block when the image is terminated; obtaining an atmospheric light value; obtaining the transmissivity of each pixel point in the preprocessed RGB image; obtaining the brightness value of each pixel point; obtaining a characteristic value of each pixel point; obtaining a suspected damaged area; determining whether the pixel point is a damaged pixel point; and obtaining a damaged area through the determined damaged pixel points. The invention adopts the image-based method to carry out damage detection, and has the effects of high detection speed and high accuracy.
Description
Technical Field
The invention relates to the field of automobile film damage detection, in particular to an automobile film damage detection method.
Background
The automobile film mainly has the functions of blocking ultraviolet rays, blocking partial heat, decorating the appearance of a vehicle and the like. However, when the automobile film is damaged or broken during the production and sale processes, the damaged film may be stuck to the surface of the automobile due to human detection negligence, which may affect the appearance of the automobile film and may not effectively protect the surface of the automobile. Therefore, the detection of the damage of the automobile film before the film pasting is a very critical step.
When the automobile film is detected manually, the detection precision is low, comprehensive detection of the automobile film is difficult to achieve, and the method for detecting the damage of the automobile film is provided by the invention aiming at the problems of low efficiency and accuracy, large workload and the like of manual detection.
Disclosure of Invention
In order to overcome the defects of the prior art, the invention provides a method for detecting the damage of an automobile film.
In order to achieve the purpose, the invention adopts the following technical scheme that the method for detecting the damage of the automobile film comprises the following steps:
preprocessing an image of the acquired film covered on a dark background to obtain a preprocessed RGB image;
extracting a dark channel image of the preprocessed RGB image;
equally dividing the dark channel image serving as an initial sub-block into a plurality of sub-blocks, calculating the weight of each sub-block, selecting the sub-block with the maximum weight from all the sub-blocks as a new initial sub-block for equally dividing, sequentially iterating, terminating iteration when the area of the equally divided sub-block is smaller than an area threshold value, and obtaining the RGB image of the corresponding minimum sub-block when termination is performed;
obtaining atmospheric light values through channel values of each pixel point in R, G and B channels in the minimum sub-block RGB image;
obtaining the transmissivity of each pixel point in the pre-processed RGB image through the atmospheric light value and the channel value of each pixel point in the pre-processed RGB image in R, G and B channels;
processing the preprocessed RGB image to obtain the brightness value of each pixel point;
obtaining a characteristic value of each pixel point by preprocessing the transmissivity and the brightness value of each pixel point in the RGB image;
clustering all the pixel points by using the characteristic value of each pixel point to obtain a suspected damaged area;
forming a feature vector by the transmittance and the brightness value of each pixel point in the suspected damage area; forming a basic feature vector by preprocessing the transmittance average value and the brightness average value of all pixel points in the RGB image; obtaining the confidence coefficient of each pixel point in the suspected damaged area by using the obtained feature vector and the basic feature vector, and determining whether the pixel point is a damaged pixel point according to the confidence coefficient;
and obtaining a damaged area through the determined damaged pixel points.
Further, the method for detecting the damage of the automobile film utilizes the characteristic value of each pixel point to cluster all the pixel points, and the method for obtaining the suspected damaged area comprises the following steps:
clustering all pixel points in the preprocessed RGB image according to the magnitude of the characteristic value of each pixel point to obtain two clustering clusters;
calculating the mean value of the characteristic values of all the pixel points in each cluster according to the characteristic value of each pixel point, selecting the cluster with the large mean value of the characteristic values, and enabling all the pixel points in the cluster to form a suspected damaged area of the adhesive film.
Further, in the method for detecting the damage of the automobile film, the expression of the weight of each sub-block is as follows:
in the formula:represents the division intoThe weight of the individual sub-blocks,represents the division intoThe number of the individual blocks is one,,is as followsAll pixel point channels in individual blockCorresponding to the standard deviation of the channel values,is a firstAll pixel point channels in each blockThe mean value of the corresponding channel values,to representIs an R channel, a G channel or a B channel.
Further, in the method for detecting damage of the automobile film, the transmittance expression of the pixel point is as follows:
in the formula:denotes the firstThe transmittance of each of the pixels is measured by the transmittance sensor,representing pre-processed RGB imageThe channel value of each pixel point on the c channel,which is indicative of the value of the atmospheric light,to representIs an R channel, a G channel or a B channel,representing the dark channel image corresponding to the pre-processed RGB image,representing by pixel pointsA central filtering window.
Further, the method for detecting the damage of the automobile film comprises the following steps of obtaining an atmospheric light value expression through channel values of each pixel point in R, G and B channels in the RGB image of the minimum sub-block:
in the formula:in RGB image representing minimum subblockThe channel value of each pixel point on the c channel, N represents the total number of pixel points in the RGB image of the minimum sub-block,in RGB image representing minimum subblockAnd (5) each pixel point.
Further, in the method for detecting damage of the automobile film, the expression of the characterization value of the pixel point is as follows:
in the formula:representing the second in a pre-processed RGB imageThe characteristic value of each pixel point is represented,representing first in pre-processed RGB imageThe brightness value of each pixel point is calculated,a first parameter of the model is represented,representing a second parameter of the model.
Further, the method for detecting the damage of the automobile film by using the obtained feature vector and the basic feature vector to obtain the confidence of each pixel point in the suspected damaged area comprises the following steps:
calculating the similarity of the feature vector and the basic feature vector of each pixel point in the suspected damaged area according to the obtained feature vector and the basic feature vector;
and obtaining the confidence of each pixel point in the suspected damaged area according to the similarity of the feature vector of each pixel point in the suspected damaged area and the basic feature vector.
Further, in the method for detecting damage of the automobile film, the similarity expression between the feature vector of each pixel point in the suspected damaged area and the basic feature vector is as follows:
in the formula:indicating a suspected damaged areaThe similarity between the feature vector of each pixel and the basic feature vector,the base feature vector is represented by a vector of features,indicating a suspected damaged areaThe feature vectors of the individual pixels are then,a feature vector is represented.
Further, in the method for detecting damage of the automobile film, the expression of the confidence of each pixel point in the suspected damage area is as follows:
in the formula:indicating a suspected damaged areaThe confidence of each of the pixel points is calculated,representing confidence model parameters.
The beneficial effects of the invention are: the method carries out damage detection on the automobile film based on the image data, extracts the damaged area based on the transmissivity and the brightness information of each pixel point, establishes a damage confidence coefficient analysis model to carry out damage judgment on the pixel points in the damaged area again, can realize accurate detection on the damage condition of the surface of the automobile film, simultaneously carries out damage detection on the automobile film by adopting an image-based method, can avoid the secondary damage to the surface of the film caused by artificial contact, and has the effects of high detection speed, high accuracy and the like.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without creative efforts.
Fig. 1 is a schematic flow chart of the present embodiment.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be obtained by a person skilled in the art without making any creative effort based on the embodiments in the present invention, belong to the protection scope of the present invention.
Example 1
An embodiment of a method for detecting a damaged film of an automobile of the present invention, as shown in fig. 1, includes:
the applicable scenarios of the embodiment are as follows: the colorless frosted automobile film is subjected to damage detection or comprehensive damage detection on the film before the automobile film is adhered. This embodiment is mainly applicable to and carries out the damage detection to colourless dull polish car pad pasting.
101. And obtaining a pre-processing RGB image.
Preprocessing the image covered on the dark background by the acquired film to obtain a preprocessed RGB image;
the embodiment mainly carries out damage detection to colorless dull polish pad pasting based on the characteristic information of the pixel of the image of gathering, consequently, this embodiment will wait to detect the pad pasting and cover on a dark background, then wait to detect the pad pasting top and deploy image acquisition equipment, carry out image acquisition to car glass pad pasting surface through the camera to follow-up damaged area to the pad pasting carries out accurate discernment. For the setting of the camera position and the camera shooting range, the implementer sets the setting according to the actual situation. In this embodiment, the camera is located right above the surface of the to-be-detected film, and collects an orthographic view of the surface of the to-be-detected film, and the dark background implementer can select the dark background by himself or herself in the actual application process, and the dark background is set to be a pure black background in this embodiment.
After the front-view image of the surface of the film to be detected is collected, because of more noise in the environment, a large amount of image noise points are generated in the image collection process, and the quality of the image on the surface of the film is influenced. The preprocessing comprises image filtering denoising and image equalization processing, an implementer can select a corresponding existing image preprocessing method, the Gaussian filter is adopted to perform noise removal on the image, and histogram equalization is adopted to process the image so as to eliminate the problems of uneven illumination on the surface of the collected film. The specific pretreatment process is a known technology, and the embodiment is not described in detail.
Therefore, the high-quality image to be detected of the film can be obtained according to the method and used as a subsequent image to be detected for analyzing the image on the surface of the film so as to identify the damaged area.
The main purpose of this embodiment is to detect the damaged condition of the surface of the film through the image data, and therefore, to the image data obtained in the above steps, this embodiment will establish a damaged detection model of the film, and construct a pixel feature vector based on the transmittance and luminance value information of each pixel, so as to perform cluster analysis on each pixel, and realize extraction of the damaged area, the damaged detection model of the film is specifically:
102. dark channel images are extracted.
For the preprocessed RGB image data, the transmittance of each pixel point is extracted and analyzed first in this embodiment, and the extracted and analyzed transmittance is used as a characteristic parameter for detecting the damage of the automobile glass film, specifically:
in this embodiment, the film is analyzed as a fog, and a model is formed according to an existing fog map, so that the image model acquired in this embodiment after being preprocessed may be represented as:
in the formula:representing a pre-processed RGB image, i.e. a hazy image,which represents a black background image when the patch is not covered, i.e., a fog-free image, which is an RGB image obtained by image-capturing and processing a dark background in the same environment when the patch is not placed, a represents an atmospheric light value,representing a pixelTransmittance at the point.
Further, carrying out deformation processing on the preprocessed image model:
then, carrying out minimum operation twice on the images in the deformed model to obtain a final processing model:
in the formula:to be pixel pointsA filter window that is the center of the filter,as an imageFirst, theThe pixel value (i.e., channel value) of each pixel point on the c channel, c represents the R channel, G channel or B channel,as an imageFirst, theThe channel value of each pixel point in the c channel.
Then, the embodiment performs dark channel processing on the dark background image when the film is not covered to obtain a corresponding dark channel image:
in the formula:as an imageThe corresponding dark channel image, x is the pixel point in the dark channel image,as an imageFirst, theAnd the channel value of each pixel point on the c channel.
103. The RGB image of the smallest subblock is obtained.
According to the dark channel prior algorithm, the method comprises the following steps:
namely, the method comprises the following steps:
according to the dark channel prior and the final processing model, a transmittance formula of each pixel point in the film pasting image to be detected (the pre-processed RGB image) can be obtained:
in the formula:representing the dark channel image corresponding to the image to be detected of the pre-processed film,indicating the atmospheric light value.
Then, calculating the atmospheric light value, wherein the calculation of the atmospheric light value is set as follows:
extracting a dark channel image of the preprocessed RGB image;
equally dividing the dark channel image serving as an initial sub-block into a plurality of sub-blocks, calculating the weight of each sub-block, selecting the sub-block with the maximum weight from all the sub-blocks as a new initial sub-block for equally dividing, sequentially iterating, terminating iteration when the area of the equally divided sub-block is smaller than an area threshold value, and obtaining the RGB image of the corresponding minimum sub-block when termination is performed;
first, the dark channel image isAre divided into a plurality of sub-blocks, set by the implementer, and the embodiment is set to divide the dark channel image intoSub-block, setting sub-block weight calculation model:
in the formula:represents the division intoThe weight of the individual sub-block is,represents the division intoThe number of the individual blocks is one,,is a firstAll pixel point channels in individual blockCorresponding to the standard deviation of the channel values,is a firstAll pixel point channels in each blockThe mean value of the corresponding channel values,representIs an R channel, a G channel or a B channel.
The higher the weight of the sub-block is, the higher the brightness value of the corresponding sub-block is, and the smaller the gradient change of the pixel value of the pixel point in the sub-block is.
Further, the sub-block with the largest weight is processed againSub-block division, calculating the weight of each sub-block according to the weight calculation model, setting the sub-block division termination condition, stopping sub-block division when the divided sub-block area is less than the area threshold value, wherein the sub-block area is the number of pixels in the sub-blockThe sum of the numbers, the area threshold can be set by the operator. At this point, the minimum subblock corresponding to the end of subblock division can be obtained and recorded as. Then the dark channel imageMinimum subblock of (1)Setting the pixel value of the corresponding pixel point to 1, setting the pixel values of the pixel points at other positions to zero, and acquiring the dark channel imageThe corresponding binary image, the binary image and the image to be detectedMultiplying to obtain the image to be detectedAnd the corresponding minimum sub-block (the RGB image corresponding to the minimum sub-block) is used as an ROI (region of interest) for calculating the atmospheric light value.
104. And obtaining the atmospheric light value.
Obtaining atmospheric light values through channel values of each pixel point in R, G and B channels in the minimum sub-block RGB image;
based on this, the atmospheric light value is calculated:
in the formula:which is indicative of the value of the atmospheric light,RGB image (i.e. ROI area) representing minimum sub-blockThe pixel value of each pixel point on a c channel, wherein c represents an R channel, a G channel or a B channel, N represents the total number of the pixel points in the RGB image of the minimum subblock,in RGB image representing minimum subblockAnd (6) each pixel point.
Therefore, the atmospheric light value during image acquisition can be calculated and used for calculating and analyzing the transmissivity of the image pixel points.
105. And obtaining the transmissivity of each pixel point.
Obtaining the transmissivity of each pixel point in the pre-processed RGB image through the atmospheric light value and the channel value of each pixel point in the pre-processed RGB image in R, G and B channels;
substituting the obtained atmospheric light value into the transmittance formula of the pixel points to calculate the transmittance of each pixel point in the image to be detected of the filmThe characteristic parameters are used as the characteristic parameters of the pixel points and are used for identifying and detecting the damage of the adhesive film;
106. and obtaining the brightness value of each pixel point.
Processing the preprocessed RGB images to obtain the brightness value of each pixel point;
further, in the embodiment, when the to-be-detected automobile film is covered on the black background, the brightness value of the acquired image is integrally improved due to the covering of the frosted film, and for the to-be-detected film image after pretreatment, HSV conversion is performed on the to-be-detected film image to obtain the brightness value of each pixel pointThe HSV is used as a characteristic parameter for detecting the breakage of the film, the known technology is converted from HSV, and relevant explanation is not provided in the embodiment;
107. and obtaining the characteristic value of each pixel point.
Obtaining a characteristic value of each pixel point by preprocessing the transmissivity and the brightness value of each pixel point in the RGB image;
and finally, establishing a pixel point characteristic value based on the characteristic parameters, wherein the pixel point characteristic value is used for carrying out characteristic description on the pixel point and is as follows:
in the formula:representing first in pre-processed RGB imageThe characteristic value of each pixel point is represented,representing first in pre-processed RGB imageThe transmittance of the individual pixels is determined,representing first in pre-processed RGB imageThe brightness value of each pixel point is calculated,a first parameter of the model is represented,representing second parameters of the modelSet by the implementer, the embodiment sets it to. The higher the characterization value of the pixel point is, the higher the possibility of being classified as a damaged pixel point is.
Therefore, based on the method of the embodiment, the feature vectors of the pixel points of the image to be detected can be extracted for identifying the damaged area.
108. A suspected damaged area is obtained.
Clustering all the pixel points by using the characteristic value of each pixel point to obtain a suspected damaged area;
after the characteristic value of each pixel point is obtained based on the method, the embodiment performs cluster analysis on each pixel point based on the characteristic value, and obtains different cluster categories to realize identification of the damaged area. The existing clustering algorithm is many, the clustering process is the existing known technology, the clustering process is not in the protection range of the embodiment and is not elaborated, an implementer can select the clustering algorithm by himself, the embodiment adopts K-means to perform clustering analysis, the implementer of the K value sets the K value to be K =2 by himself, and the embodiment sets the K value to be K =2. For two cluster categories, the present embodiment will calculate the mean value of the characterization values of all the pixels in the two categoriesWherein Z is the number of pixel points in the corresponding category,the representative category is a category of the user,representIn the category ofAfter obtaining the mean value of the characterization values corresponding to the two categories for each pixel, this embodiment will provide a mean value of the characterization values corresponding to the two categoriesThe category with the larger average value is used as the category corresponding to the damage of the film, each connected domain formed by the pixel points contained in the category is used as a suspected damaged area, and the other category is the category corresponding to the normal film, so that the suspected damaged area on the surface of the film can be extracted.
109. It is determined whether the pixel is a broken pixel.
Forming a feature vector by the transmittance and the brightness value of each pixel point in the suspected damage area; forming a basic feature vector by preprocessing the transmittance average value and the brightness average value of all pixel points in the RGB image; obtaining the confidence coefficient of each pixel point in the suspected damaged area by using the obtained feature vector and the basic feature vector, and determining whether the pixel point is a damaged pixel point according to the confidence coefficient;
through the clustering process, a suspected damaged area can be preliminarily obtained, further, damage confidence degree analysis is performed on all the pixel points in the suspected damaged area again, and only the extracted pixel points in the suspected damaged area are subjected to damage confidence degree analysis, so that the calculation amount can be effectively reduced, calculation of irrelevant pixel points is avoided, and the precision of damage identification is ensured. For an image to be detected, firstly, obtaining a characteristic parameter mean value of all pixel points in the image to be detectedAndconstructing a base feature vectorAnd the method is used for calculating the damage confidence of each pixel point in the suspected damage area. And then calculating the similarity between the feature vector of each pixel point in the suspected damaged area and the basic feature vector:
in the formula:indicating a suspected damaged areaThe similarity between the feature vector of each pixel and the basic feature vector,the base feature vector is represented by a vector of features,indicating a suspected damaged areaThe feature vectors of the individual pixels are then,,the feature vector is represented.
The larger the function value is, the more similar the function value is, and the smaller the possibility that the corresponding pixel point is damaged is. Establishing a damage confidence coefficient model based on the similarity index, and calculating the damage confidence coefficient of the pixel points in the suspected damage area, wherein the damage confidence coefficient model is as follows:
in the formula:indicating a suspected damaged areaThe confidence of the damage to an individual pixel point,the confidence model parameter is represented, and the embodiment sets the confidence model parameter to be 0.5, which can be set by an implementer. Normalizing the model to ensure that the function value is [0,1], wherein the higher the function value of the model is, the greater the damage confidence of the corresponding pixel point is, the embodiment calculates the damage confidence of each pixel point in the suspected damage area, and sets a confidence thresholdAnd when the damage confidence coefficient is higher than the threshold value, the confidence coefficient of the pixel point which is the damage pixel point is considered to be higher, the pixel point is taken as the damage pixel point, and otherwise, the pixel point is a normal pixel point. The confidence threshold is set by the implementer, and the embodiment sets the confidence threshold as the implemented confidence。
110. A damaged area is obtained.
And obtaining a damaged area through the determined damaged pixel points.
Therefore, all the pixel points of the image to be detected can be classified and judged, and the damage condition of the surface of the film can be analyzed. The damage condition of each pixel point is judged based on the extracted feature vectors of the pixel points, the damaged area can be accurately extracted, the damaged position and the damaged area on the surface of the film can be prompted, reference opinions can be provided for relevant operators, and the repair processing of the film by the operators is facilitated.
The method carries out damage detection on the automobile film based on the image data, extracts the damaged area based on the transmissivity and the brightness information of each pixel point, establishes a damage confidence coefficient analysis model to carry out damage judgment on the pixel points in the damaged area again, can realize accurate detection on the damage condition of the surface of the automobile film, simultaneously carries out damage detection on the automobile film by adopting an image-based method, can avoid the secondary damage to the surface of the film caused by artificial contact, and has the effects of high detection speed, high accuracy and the like.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that fall within the spirit and principle of the present invention are intended to be included therein.
Claims (9)
1. A method for detecting damage of an automobile film is characterized by comprising the following steps:
preprocessing the image covered on the dark background by the acquired film to obtain a preprocessed RGB image;
extracting a dark channel image of the preprocessed RGB image;
equally dividing the dark channel image serving as an initial sub-block into a plurality of sub-blocks, calculating the weight of each sub-block, selecting the sub-block with the maximum weight from all the sub-blocks as a new initial sub-block for equally dividing, sequentially iterating, terminating iteration when the area of the equally divided sub-block is smaller than an area threshold value, and obtaining the RGB image of the corresponding minimum sub-block when termination is performed;
obtaining an atmospheric light value through channel values of each pixel point in R, G and B channels in the RGB image of the minimum subblock;
obtaining the transmissivity of each pixel point in the pre-processed RGB image through the atmospheric light value and the channel value of each pixel point in the pre-processed RGB image in R, G and B channels;
processing the preprocessed RGB image to obtain the brightness value of each pixel point;
obtaining a characteristic value of each pixel point by preprocessing the transmissivity and the brightness value of each pixel point in the RGB image;
clustering all the pixel points by using the characterization value of each pixel point to obtain a suspected damaged area;
forming a feature vector by the transmittance and the brightness value of each pixel point in the suspected damage area; forming a basic feature vector by preprocessing the transmittance average value and the brightness average value of all pixel points in the RGB image; obtaining the confidence coefficient of each pixel point in the suspected damaged area by using the obtained feature vector and the basic feature vector, and determining whether the pixel point is a damaged pixel point according to the confidence coefficient;
and obtaining a damaged area through the determined damaged pixel points.
2. The method for detecting the damage of the automobile film according to claim 1, wherein the method for clustering all the pixels by using the characterization value of each pixel to obtain the suspected damaged area comprises the following steps:
clustering all pixel points in the preprocessed RGB image according to the magnitude of the characteristic value of each pixel point to obtain two clustering clusters;
calculating the mean value of the characteristic values of all the pixel points in each cluster through the characteristic values of all the pixel points, selecting the cluster with the large mean value of the characteristic values, and enabling all the pixel points in the cluster to form a suspected damaged area of the film.
3. The method for detecting the damage of the automobile film according to claim 1, wherein the expression of the weight of each sub-block is as follows:
in the formula:represents the division intoThe weight of the individual sub-block is,represents the division intoThe number of the individual blocks is one,,is as followsAll pixel point channels in each blockCorresponding to the standard deviation of the channel values,is as followsAll pixel point channels in individual blockThe mean value of the corresponding channel values,representIs an R channel, a G channel or a B channel.
4. The method for detecting the damage of the automobile film according to claim 1, wherein the transmittance expression of the pixel points is as follows:
in the formula:denotes the firstThe transmittance of the individual pixels is determined,representing pre-processed RGB imagesThe channel value of each pixel point on the c channel,which is indicative of the value of the atmospheric light,representIs an R channel, a G channel or a B channel,representing the dark channel image corresponding to the pre-processed RGB image,is expressed in pixel pointsA central filtering window.
5. The automobile film sticking damage detection method according to claim 4, wherein an expression of the atmospheric light value obtained by the channel value of each pixel point in the R, G and B channels in the minimum sub-block RGB image is as follows:
6. The method for detecting the damage of the automobile film according to claim 1, wherein the expression of the characterization value of the pixel point is as follows:
in the formula:representing the second in a pre-processed RGB imageThe characteristic value of each pixel point is represented,representing first in pre-processed RGB imageThe brightness value of each pixel point is calculated,a first parameter of the model is represented,representing a second parameter of the model.
7. The method for detecting the damage of the automobile film according to claim 1, wherein the method for obtaining the confidence of each pixel point in the suspected damaged area by using the obtained feature vector and the basic feature vector comprises the following steps:
calculating the similarity of the feature vector and the basic feature vector of each pixel point in the suspected damage area according to the obtained feature vector and the basic feature vector;
and obtaining the confidence of each pixel point in the suspected damaged area according to the similarity of the feature vector of each pixel point in the suspected damaged area and the basic feature vector.
8. The method for detecting the damage of the automobile film according to claim 7, wherein the expression of the similarity between the feature vector of each pixel point in the suspected damaged area and the basic feature vector is as follows:
in the formula:indicating a suspected damaged areaThe similarity between the feature vector of each pixel and the basic feature vector,the base feature vector is represented by a vector of features,indicating a suspected damaged areaThe feature vectors of the individual pixels are then,the feature vector is represented.
9. The method for detecting the damage of the automobile film according to claim 8, wherein the confidence of each pixel point in the suspected damage area is expressed as:
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