CN115631173A - Composite film defect identification method - Google Patents
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Abstract
The invention relates to the technical field of defect identification, in particular to a composite film defect identification method, which comprises the following steps: acquiring a surface gray level image of the composite film, and determining the composite film image suspected of having defects according to the gray level value; segmenting the image to obtain a suspected defect area; obtaining a gray level deviation index of a pixel point according to the gray level value difference between a central pixel point in a window with a set size and other pixel points in the window; dividing the pixel points into three grades according to the gray deviation index, determining possible defect pixel points, and performing region growth by using the possible defect pixel points to obtain possible defect regions; the method comprises the steps of obtaining end points of a line segment where the principal component direction of the possible defect area is located, obtaining a non-connectivity index according to the distance between the end points corresponding to the possible defect area, determining a connected area according to the non-connectivity index and an index threshold value, and identifying the defect of the composite film according to the connected area.
Description
Technical Field
The invention relates to the technical field of defect identification, in particular to a composite film defect identification method.
Background
The composite film is a high polymer material compounded by two or more layers of films made of different materials and is mainly used for packaging. The surface wrinkle of the composite film is a common problem in the processing and application processes of the composite flexible packaging material, the surface wrinkle problem is represented by that the film on the surface layer is convex upwards, the surface wrinkle problem can influence the aesthetic property and the quality of the composite film package, and therefore, the surface defect identification needs to be carried out on the composite film processed at each production stage to identify the wrinkle defect.
The conventional identification method is to process the surface image of the composite film by using a threshold segmentation method, but because the wrinkle defect on the surface of the composite film is mainly in an approximate tunnel shape, the gray difference is not obvious, most of the composite films are white, the threshold is influenced by the reflection condition in the presence of illumination, the image segmentation result is inaccurate, and the composite film defect identification result is also inaccurate.
Disclosure of Invention
In order to solve the above technical problems, an object of the present invention is to provide a method for identifying defects of a composite film, which adopts the following technical scheme:
acquiring a surface gray image of the composite film, and determining the composite film image suspected of having defects according to the gray value of a pixel point in the surface gray image; performing threshold segmentation on the composite film image to obtain a suspected defect area;
performing sliding window processing on the pixels in the suspected defect area by using a window with a set size, and obtaining a gray level deviation index of the pixels according to the gray level value of the central pixel in the window and the gray level value difference of other pixels in the window; dividing the pixel points into three grades according to the gray deviation index, determining possible defect pixel points according to the number of different grades in a window corresponding to the pixel points, and performing region growth by using the possible defect pixel points to obtain a possible defect region;
the method comprises the steps of obtaining end points of a line section where the principal component direction of a possible defect area is located, obtaining a non-connectivity index according to the distance between the end points corresponding to the possible defect area, determining a connected area according to the non-connectivity index and an index threshold value, and identifying the defect of the composite film according to the connected area.
Preferably, the determining the composite film image suspected of having the defect according to the gray value of the pixel point in the surface gray image specifically includes:
and calculating a color second moment of the image according to the gray value of the pixel point in the surface gray image, obtaining a color characteristic value corresponding to the surface gray image according to the color second moment, and marking the surface gray image with the color characteristic value larger than a color threshold value as a composite film image suspected of having defects.
Preferably, the obtaining of the suspected defect area by performing threshold segmentation on the composite film image specifically includes:
constructing a gray level histogram according to gray levels of pixel points in the composite film image, acquiring gray levels corresponding to two wave troughs in the gray level histogram, recording a smaller gray level corresponding to the two wave troughs as a first segmentation threshold, and recording a larger gray level corresponding to the two wave troughs as a second segmentation threshold; and the area formed by the pixel points with the gray value smaller than the first segmentation threshold and the area formed by the pixel points with the gray value larger than the second segmentation threshold are suspected defect areas.
Preferably, the method for obtaining the gray level deviation index specifically includes:
wherein,
the gray scale deviation index corresponding to the z-th pixel point is shown,
represents the gray value of the z-th pixel point,
representing the gray value of the first other pixel in the window where the z-th pixel is located,
representing the gray value of the jth pixel point in the window where the jth pixel point is located,
representing the total number of other pixels except the center point within the window, exp () represents an exponential function with a natural constant e as the base.
Preferably, the dividing the pixel points into three levels according to the gray scale deviation index specifically includes: and acquiring a difference value between the gray level deviation indexes of any two pixel points, and dividing all the pixel points into three levels based on all the difference values.
Preferably, the determining the possible defective pixel points according to the number of different levels in the window corresponding to the pixel points specifically includes:
for any pixel point in a window, if three levels of pixel points exist in all pixel points in the window, the any pixel point is a possible defect pixel point; if the pixel points of the three grades do not exist, the window is enlarged according to the set step length, if the pixel points of the three grades exist in all the pixel points in the enlarged window, any one pixel point is a possible defect area, and if the pixel points of the three grades do not exist in all the pixel points in the enlarged window, any one pixel point is a noise pixel point.
Preferably, the determining the connected region according to the non-connectivity index and the index threshold specifically includes:
when the non-connectivity indexes corresponding to the end points of the possible defect area are all smaller than the index threshold value, connecting the possible defect area with the possible defect area corresponding to the non-connectivity index smaller than the index threshold value; when the non-connectivity index corresponding to one end point of the possible defect area is smaller than the index threshold, calculating the shortest distance from the other end point to the edge of the composite film image, if the shortest distance is smaller than the index threshold, connecting the possible defect area with the possible defect area corresponding to the non-connectivity index smaller than the index threshold, and if the shortest distance is greater than or equal to the index threshold, discarding the possible defect area without connection; when the non-connectivity indexes corresponding to the end points of the possible defect areas are not less than the index threshold, the possible defect areas are discarded and are not connected; all connected regions constitute a connected region.
The embodiment of the invention at least has the following beneficial effects:
determining a composite film image suspected of having defects according to gray values of pixel points in the image, roughly analyzing the image by combining color distribution characteristics in the image, screening out the image with the defects, and carrying out subsequent further judgment; then, the composite film image is processed by using the window, the gray scale deviation index of the pixel point is calculated, the possible defect pixel point is obtained according to the gray scale deviation index, and the gray scale difference condition of the pixel point in the neighborhood is considered by analyzing the gray scale difference of the pixel point in the window range, so that more accurate defect information can be obtained; and finally, connecting all the defect areas according to the connectivity among the defect areas to further obtain a defect identification result, considering the shape characteristics of the defects of the composite film, namely the connectivity to a certain degree, further increasing the accuracy of the obtained defect areas and enabling the defect identification result to be more accurate.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions and advantages of the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.
FIG. 1 is a flow chart of a method for identifying defects of a composite film according to the present invention.
Detailed Description
To further illustrate the technical means and effects of the present invention adopted to achieve the predetermined objects, the following detailed description of the method for identifying defects of a composite film according to the present invention, its specific implementation, structure, features and effects will be given in conjunction with the accompanying drawings and the preferred embodiments. In the following description, different "one embodiment" or "another embodiment" refers to not necessarily the same embodiment. Furthermore, the particular features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.
The following describes a specific scheme of the composite film defect identification method provided by the invention in detail with reference to the accompanying drawings.
Example (b):
the main purposes of the invention are: and (3) carrying out surface defect detection on the composite film after the composite film is processed at each production stage by an image processing technology, wherein the defects are mainly wrinkle defects.
The specific scenes aimed by the invention are as follows: and (4) performing wrinkle defect detection after the compound film is processed by a machine, after curing, when the bag making processing is finished and after a period of time of placement, when the water boiling processing is finished and after a period of time of placement, when the boiling processing is finished and after a period of time of placement.
Referring to fig. 1, a flowchart of a method for identifying defects of a composite film according to an embodiment of the present invention is shown, where the method includes the following steps:
acquiring a surface gray image of a composite film, and determining the composite film image suspected of having defects according to the gray value of a pixel point in the surface gray image; and performing threshold segmentation on the composite film image to obtain a suspected defect area.
Firstly, after the composite film is processed by a film making machine, after curing treatment, when bag making processing is finished and after a period of time of placement, when boiling treatment is finished and after a period of time of placement, image acquisition is carried out at each stage, and the surface image of the composite film is obtained. Because the acquisition process is influenced by mechanical noise, the acquired surface image of the composite film is subjected to noise reduction treatment. In this embodiment, a gaussian filtering method is used to perform noise reduction on the surface image, then a semantic segmentation method is used to remove the interference of the background, and finally the image obtained after the semantic segmentation is subjected to graying processing to obtain a surface grayscale image of the composite film.
It should be noted that, in order to reduce the amount of calculation, image analysis needs to be performed on the images acquired at each stage, that is, whether a wrinkle defect exists in the surface gray-scale image of the composite film corresponding to the current stage is determined in advance according to the gray-scale features in the images, so that only the surface gray-scale image with the wrinkle defect is subjected to subsequent analysis.
When the composite film has a wrinkle defect, a convex tunnel-shaped wrinkle appears on the surface of the composite film, and the area where the wrinkle exists is shown in an image, the color of the convex part in the wrinkle part is bright and white, but the color of the concave parts on two sides of the convex part is dark and gray. From this, it was found that if wrinkle defects exist on the surface of the composite film, bright white and dark gray appear in the surface tone image of the composite film due to the generation of wrinkle defects.
Based on this, carry out analysis according to the grey scale characteristic of pixel in the surface gray scale image of composite film, judge the color distribution range in the surface gray scale image of composite film, when the composite film does not have the fold defect, the grey scale value in the surface gray scale image of composite film is all comparatively close, shows as a comparatively close colour value, and when the composite film has the fold defect, can increase the colour that two kinds of grey scale values are different in the surface gray scale image of composite film, shows as three colour values in the image.
Then, since the color moment is a simple and effective color feature labeling method, and the color second moment can represent the distribution range of the color in the image, in this embodiment, the color second moment of the image is calculated based on the gray value of the pixel point in the surface gray image of the composite film
Is formulated as:
wherein,
and expressing the gray value of the ith pixel point in the surface gray image of the composite film, and N expressing the total number of the pixel points in the surface gray image. And calculating the difference value between the gray value of each pixel point and the image gray mean value in the formula, reflecting the deviation degree of each pixel point relative to the image gray mean value, summing the deviation degrees of all the pixel points, and averaging to express the size of the color distribution range of the surface gray image. When in use
The larger the image color distribution range, the wider the image color distribution range, the more various color values may exist in the surface gray level image, otherwise
The smaller the size, i.e. the narrower the color distribution range of the representative image, the more the surface gray scale map is illustratedThere may be fewer color values in the image, i.e., there may be one color value.
In this embodiment, the color second moment obtained based on the gray value of the pixel point in the surface gray image of the composite film
Performing normalization processing, namely obtaining the color characteristic value of the surface gray level image according to the color second moment, and expressing the color characteristic value as
Wherein
in order to obtain a color characteristic value after normalization processing is carried out on the color second moment,
is the second moment of the color of the image, and e is a natural constant.
When in use
The larger the value of (a) is,
the larger the value of (A) is, the wider the distribution range of the expressed image color is, which indicates that more color values may exist in the surface gray level image, the wrinkle defect may exist on the surface of the composite film corresponding to the image, otherwise, when the color value of (A) is larger, the wrinkle defect may exist on the surface of the composite film corresponding to the image
The smaller the size of the product is,
the smaller the value of (b), that is, the narrower the distribution range of the representative image color, indicates that there may be fewer color values in the surface gray image, that is, there may be one color value, and there may be no wrinkle defect on the surface of the composite film corresponding to the image.
Setting color threshold, in this embodimentThe value of (3) is 0.4, when the value of the color characteristic value corresponding to the surface gray level image is greater than the color threshold value, that is, the value is
In the case of the composite film image, the color distribution range in the surface gray level image is large, and the wrinkle defect may exist, so that the surface gray level image is marked as the composite film image suspected of having the defect. When the value of the color characteristic value corresponding to the surface gray level image is less than or equal to the color threshold value, that is to say
In the present embodiment, the surface gray image of the composite film having the color feature value less than or equal to the color threshold is not subjected to the subsequent analysis because the color distribution range in the surface gray image is narrow and the wrinkle defect may not exist.
Finally, in the area where the wrinkles exist on the composite film image, the raised parts on the wrinkles are bright white due to light reflection, and the bottoms of the mountain roots at the two sides of the raised parts on the wrinkles are shaded dark gray due to the shielding of the raised parts. All the areas where wrinkles exist referred to in this embodiment include a raised bright white portion and a dark gray-shaded portion at the bottom of mountain roots on both sides of the raised portion.
Based on the above, a gray level histogram is constructed according to gray levels of pixel points in the composite film image suspected of having the defect, and the composite film image is segmented to obtain a suspected defect area by taking the gray levels corresponding to two troughs in the gray level histogram as segmentation thresholds.
Specifically, the gray values corresponding to two troughs in the gray histogram are used as segmentation thresholds, the gray value corresponding to the two troughs is smaller and is used as a first segmentation threshold, the gray value corresponding to the two troughs is larger and is used as a second segmentation threshold, the image is segmented into three regions by using the first segmentation threshold and the second segmentation threshold, the first segmentation threshold is used as a segmentation point between a dark gray shadow part and a dominant color part of the composite film, so that a region formed by pixel points of which the gray values are smaller than the first segmentation threshold is used as a wrinkle convex region, and the second segmentation threshold is used as a segmentation point between the dominant color part of the composite film and a bright white convex part, so that a region formed by pixel points of which the gray values are larger than the second segmentation threshold is used as a wrinkle convex region. And the area formed by the pixel points of which the gray value is greater than or equal to the first segmentation threshold and less than or equal to the second segmentation threshold is a normal area, and no wrinkle defect exists in the normal area. Wherein, the fold raised area and the fold shadow area form a suspected defect area.
Performing sliding window processing on the pixels in the suspected defect area by using a window with a set size, and obtaining a gray level deviation index of the pixels according to the gray level value of the central pixel in the window and the gray level value difference of other pixels in the window; dividing the pixel points into three grades according to the gray deviation index, determining possible defect pixel points according to the quantity of different grades in a window corresponding to the pixel points, and performing region growth by using the possible defect pixel points to obtain a possible defect region.
Firstly, it should be noted that the area where the wrinkle exists includes a convex portion on the wrinkle and a root bottom shadow portion on two sides of the convex portion on the wrinkle, the composite film image is processed by using a window with a set size, sliding is started from left to right and from top to bottom from the upper left corner of the composite film image, the sliding step length is 1, when the composite film image slides to a position, the area where the pixel belongs to is judged according to the gray value of the pixel at the center position of the window, and when the pixel at the center position belongs to a possible defect area, the pixel distribution characteristics in the window are analyzed.
When the pixel point at the central position belongs to the possible defect area, namely the pixel point belongs to the wrinkle convex area or the wrinkle shadow area, the wrinkle defect exists in the window, the convex part and the shadow part in the wrinkle exist at the same time and are distributed in a centralized manner, and then in the window with a certain size, the pixel point belongs to the wrinkle convex area and the wrinkle shadow area, which is shown in color distribution, the gray value of the pixel point in the window can exist in two intervals, namely, the gray value is smaller than the first segmentation threshold value and larger than the second segmentation threshold value, namely, the bright white pixel point and the dark gray pixel point exist. After the size of the window is enlarged, the window contains a normal area of the composite film except for the defect part, three color distributions necessarily exist in the window, namely the gray value of the pixel points in the window exists in three intervals. Meanwhile, the pixel points of the three color distributions in the window are not distributed in disorder, but are distributed in three regions in a concentrated manner.
In this embodiment, the value of the set size is 3*3, which can be set by an implementer according to the actual situation.
Then, a window 3*3 is used for processing a possible defect area in the composite film image, for any pixel point, in a window 3*3 taking the pixel point as a center, if a wrinkle area exists in the window, gray value differences of the pixel point at the center position in the window and other pixel points are respectively calculated, and the pixel deviation condition of the pixel point at the center position can be obtained according to the difference between each difference.
Obtaining the gray scale deviation index of the pixel point according to the gray scale value of the central pixel point in the window and the gray scale value difference of other pixel points in the window, and expressing the gray scale deviation index by a formula as follows:
wherein,
indicating the gray scale deviation index corresponding to the z-th pixel point,
the gray value of the z-th pixel point is represented,
representing the gray value of the first other pixel in the window where the z-th pixel is located,
representing the gray value of the jth pixel point in the window where the jth pixel point is located,exp () represents an exponential function with a natural constant e as the base,
the total number of other pixels except the center point in the representation window is 8 in this embodiment.
The smaller the gray value difference between the pixel points is, the smaller the corresponding gray value difference is, which indicates that there may be no wrinkle defect in the window where the pixel point is located, the smaller the deviation degree between the gray value differences is, the smaller the value of the gray value deviation index of the pixel point is, which indicates that the pixel point is more likely to belong to a normal pixel point on the composite film image. The larger the gray value difference between the pixel points is, the larger the corresponding gray value difference is, which indicates that a window where the pixel point is located may have a wrinkle defect, and the larger the deviation degree between the gray value differences is, the larger the value of the gray value deviation index of the pixel point is, which indicates that the pixel point is more likely to belong to the pixel point in the possible defect region on the composite film image.
And finally, respectively calculating the gray level deviation indexes of all pixel points in the possible defect area on the composite film image according to the method, acquiring the difference value between the gray level deviation indexes of any two pixel points, and dividing all the pixel points into three grades based on all the difference values.
Specifically, any two pixel points are selected to be marked as a first pixel point and a second pixel point, the difference value of the gray scale deviation indexes corresponding to the two pixel points is calculated, if the value of the difference value is greater than a threshold value, the two pixel points are considered to be more unlikely to belong to the pixel point in the same region, and therefore the gray scale deviation indexes corresponding to the two pixel points are divided into two different levels; if the value of the difference is smaller than or equal to the threshold, the two pixel points are considered to possibly belong to the pixel points in the same region, so that the gray level deviation indexes corresponding to the two pixel points are divided into the same grade.
And then, one other pixel point is selected arbitrarily to be marked as a third pixel point, the difference value of the gray scale deviation index corresponding to the third pixel point and the gray scale deviation index corresponding to the first pixel point is calculated respectively, and the difference value of the gray scale deviation index corresponding to the third pixel point and the gray scale deviation index corresponding to the second pixel point is calculated. If the difference value is smaller than or equal to the threshold value, namely the difference value of the gray scale deviation index corresponding to the third pixel point and the first pixel point is smaller than or equal to the threshold value, dividing the gray scale deviation index corresponding to the third pixel point into the grade of the gray scale deviation index corresponding to the first pixel point, or dividing the gray scale deviation index corresponding to the third pixel point into the grade of the gray scale deviation index corresponding to the second pixel point, wherein the difference value of the gray scale deviation index corresponding to the third pixel point and the gray scale deviation index corresponding to the second pixel point is smaller than or equal to the threshold value. And if the difference is not smaller than or equal to the threshold, namely the difference between the gray scale deviation indexes of the third pixel point and the other two pixel points is larger than the threshold, dividing the gray scale deviation index corresponding to the third pixel point into a third grade. In this embodiment, the value of the threshold is 0.2, and an implementer can set the threshold according to actual conditions.
Based on the above, by analogy, all the pixel points are divided into three levels based on all the difference values, the graded standard is that the level with the minimum gray scale deviation index is divided into a first level, the level with the larger gray scale deviation is divided into a second level, and the level with the maximum gray scale deviation is divided into a third level. If the composite film image has a wrinkle defect, the color distribution of the pixel points in the image is definitely represented by three colors, and the gray scale deviation index corresponding to the pixel points in the image is definitely divided into three levels. Meanwhile, each pixel point corresponds to one gray level deviation index, each gray level deviation index corresponds to one grade, each pixel point corresponds to one grade, and the three grades can be approximately regarded as three different areas, namely a normal area, a fold convex area and a fold shadow area.
It should be noted that, in this embodiment, by considering the deviation of the gray level difference between a pixel point and a pixel point in its neighborhood, the change condition of the gray level difference in the image can be analyzed in more detail, and the pixel point is determined based on the change condition of the difference, so that more accurate defect information can be obtained.
Further, the pixel point in the window where the pixel point is located is judged, in the window with a certain size, the pixel point belongs to a fold convex area and a fold shadow area, and the result shows that the deviation of the gray difference exists, the corresponding grade of the pixel point in the window possibly has two different grades, after the size of the window is enlarged, the window also comprises a normal area of a composite film except for a defect part, three color distributions must exist in the window, and the corresponding grade of the pixel point in the enlarged window has three different grades.
Therefore, for any pixel point in the window, if three levels of pixel points exist in all pixel points in the window, it is indicated that three pixel points in different areas possibly exist in the window where the pixel point is located, and the any pixel point is a possible defect pixel point; if the pixel points with the three grades do not exist, the window is enlarged according to the set step length, if the pixel points with the three grades exist in all the pixel points in the enlarged window, any one pixel point is a possible defect area, if the pixel points with the three grades do not exist in all the pixel points in the enlarged window, the fact that the pixel point which is judged at present does not belong to a defect part and is only a noise point is possible is indicated, and any one pixel point is a noise pixel point. In this embodiment, the value of the set step length is 2, that is, the size of the enlarged window is 5*5, and an implementer can set the value of the set step length according to an actual situation.
After the possible defect pixel points are obtained according to the method, the possible defect pixel points are respectively used as initial seed points for area growth, the area obtained by the area growth is marked as a possible defect area, wherein a rule implementer for the area growth can carry out setting according to actual conditions, for example, when the difference value between the gray values of the pixel points is smaller than a set threshold value, the growth is carried out, and the value of the set threshold value needs to be set by the implementer according to the actual conditions.
And step three, acquiring end points of a line segment where the principal component direction of the possible defect area is located, obtaining a non-connectivity index according to the distance between the end points corresponding to the possible defect area, determining a connected area according to the non-connectivity index and an index threshold, and identifying the defect of the composite film according to the connected area.
It should be noted that the wrinkle defect existing on the surface of the composite film may also be referred to as a tunnel defect because the raised portions on the wrinkles are all around and continuously converge or diverge, so as to form complete wrinkles similar to a tunnel shape, that is, the wrinkles are all interconnected and exist on the composite film, and there is no discrete distribution of the wrinkle portions. Therefore, for any possible defect region, connectivity between the possible defect region and other possible defect regions is analyzed respectively, and the confidence level that the possible defect region is a real defect region is judged according to the connectivity.
Specifically, PCA principal component analysis is performed on each possible defect region to obtain a principal component direction of each possible defect region, and two end points of a line segment where the principal component direction of the possible defect region is located are obtained, and then the two end points can be regarded as two end points of a wrinkle line segment in the possible defect region.
Because the wrinkle defect is in a tunnel shape in the image, the regions with the wrinkle defect are communicated with each other, and on the basis, whether the possible defect region is communicated with other possible defect regions is judged by judging the distance between two end points corresponding to the possible defect region and the distance between end points corresponding to other possible defect regions.
Based on this, a non-connectivity index is obtained according to the distance between the endpoints corresponding to the possible defect region, the non-connectivity indexes between the two endpoints corresponding to the possible defect region and the endpoints of the other possible defect regions are respectively recorded as a first non-connectivity index and a second non-connectivity index, that is, the two endpoints corresponding to the possible defect region respectively correspond to one non-connectivity index, which is expressed by a formula:
wherein,
representing a first non-connectivity indicator corresponding to a first end point in the possible defect region c,
represents a second non-connectivity index corresponding to a second end point in the possible defect region c, and min () represents a function for finding a minimum value.
And establishing a rectangular coordinate system taking pixel points as a unit by taking the upper left corner of the image as an origin, wherein the abscissa and the ordinate of the pixel points are the number of columns and the number of rows in the image respectively.
And
respectively showing the abscissa and ordinate of the first end point in the possible defect area c on the image of the composite film,
and
respectively representing the abscissa and ordinate of the first end point in the possible defect area c on the image,
and
respectively representing the abscissa and ordinate of the k-th end point of the other possible defect area on the image,
and
respectively, the abscissa and ordinate of the o-th end point of the other possible defect area on the image.
Meanwhile, considering that there may be a wrinkle portion located at an edge, the shortest distance between two end points corresponding to each possible defect region and the edge of the composite film image needs to be calculated and respectively recorded as a first non-edge index and a second non-edge index, and the smaller the shortest distance is, the closer the end points are to the edge of the image, the smaller the value of the corresponding non-edge index is.
Further, a connected region is determined according to the non-connectivity index and the index threshold, when the non-connectivity indexes corresponding to the end points of the possible defect region are both smaller than the index threshold, that is, the first non-connectivity index and the second non-connectivity index corresponding to the two end points of the region are both smaller than the index threshold, the possible defect region is connected with the possible defect region corresponding to the non-connectivity index smaller than the index threshold, that is, the region is connected with the possible defect region where the end point corresponding to the first non-connectivity index is located, the region is connected with the possible defect region where the end point corresponding to the second non-connectivity index is located, and the connected region is the connected region.
When the non-connectivity index corresponding to only one end point of the possible defect area is smaller than the threshold, calculating the shortest distance from the other end point to the edge of the composite film image, wherein the shortest distance is the non-marginal index corresponding to the end point, if the non-marginal index is smaller than the index threshold, connecting the possible defect area with the possible defect area corresponding to the non-connectivity index smaller than the threshold, and the connected area is a connected area.
For example, in two endpoints of a possible defect region, a first non-connectivity index corresponding to a first endpoint is smaller than an index threshold, and a second non-connectivity index corresponding to a second endpoint is larger than the index threshold, the second non-marginal index corresponding to the second endpoint is compared with the index threshold, if the second non-connectivity index is larger than or equal to the index threshold, the possible defect region is possibly a discrete region, and therefore the possible defect region needs to be discarded and not connected, and if the second non-connectivity index is smaller than the index threshold, one side of the possible defect region is connected with other possible defect regions, and the other side of the possible defect region is close to an image edge, and therefore the possible defect region needs to be connected with the possible defect region where the endpoint corresponding to the first non-connectivity index is located.
When the non-connectivity index corresponding to the end point of the possible defect area is not smaller than the index threshold, that is, the first non-connectivity index and the second non-connectivity index corresponding to the two end points of the area are not smaller than the index threshold, it is indicated that connectivity does not exist between the possible defect area and other possible defect areas, the possible defect area is a discrete area, the possible defect area is discarded, and connection is not performed.
In this embodiment, the value of the index threshold is 4, and an implementer can set the index threshold according to an actual situation.
And judging all possible defect areas according to the method, connecting the possible defect areas needing to be connected, forming a connected area by all the connected areas, and segmenting the composite film image according to the connected area so as to identify the defects of the composite film. In this embodiment, the pixel values of the pixels in the connected region are set to 255, and the pixel values of the other pixels are set to 0, so as to segment the composite film image, and perform defect identification by using the segmented image to obtain an identification result. The method for segmenting the image and the method for identifying the defect are various, and an implementer can select the method according to the actual situation.
It should be noted that, the invention analyzes the possibility that the pixel point is the pixel point of the wrinkle region first, then grows the possible wrinkle connected domain, analyzes the possibility that the possible wrinkle connected domain forms the tunnel, thereby identifies the complete wrinkle region, and overcomes the difficulty that the threshold segmentation cannot identify the wrinkle with fine gray difference.
The above-mentioned embodiments are only used for illustrating the technical solutions of the present application, and not for limiting the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; such modifications or substitutions do not cause the essential features of the corresponding technical solutions to depart from the scope of the technical solutions of the embodiments of the present application, and are intended to be included within the scope of the present application.
Claims (7)
1. A composite film defect identification method is characterized by comprising the following steps:
acquiring a surface gray image of the composite film, and determining the composite film image suspected of having defects according to the gray value of a pixel point in the surface gray image; performing threshold segmentation on the composite film image to obtain a suspected defect area;
performing sliding window processing on the pixels in the suspected defect area by using a window with a set size, and obtaining a gray level deviation index of the pixels according to the gray level value of the central pixel in the window and the gray level value difference of other pixels in the window; dividing the pixel points into three grades according to the gray level deviation index, determining possible defect pixel points according to the number of different grades in a window corresponding to the pixel points, and performing region growth by using the possible defect pixel points to obtain a possible defect region;
the method comprises the steps of obtaining end points of a line section where the principal component direction of a possible defect area is located, obtaining a non-connectivity index according to the distance between the end points corresponding to the possible defect area, determining a connected area according to the non-connectivity index and an index threshold value, and identifying the defect of the composite film according to the connected area.
2. The method according to claim 1, wherein the determining the composite film image suspected of having the defect according to the gray-scale values of the pixels in the surface gray-scale image specifically comprises:
and calculating a color second moment of the image according to the gray value of the pixel point in the surface gray image, obtaining a color characteristic value corresponding to the surface gray image according to the color second moment, and marking the surface gray image with the color characteristic value larger than a color threshold value as a composite film image suspected of having defects.
3. The method according to claim 1, wherein the step of performing threshold segmentation on the composite film image to obtain the suspected defect area specifically comprises:
constructing a gray level histogram according to gray levels of pixel points in the composite film image, acquiring gray levels corresponding to two wave troughs in the gray level histogram, recording a smaller gray level corresponding to the two wave troughs as a first segmentation threshold, and recording a larger gray level corresponding to the two wave troughs as a second segmentation threshold; and the area formed by the pixel points with the gray value smaller than the first segmentation threshold and the area formed by the pixel points with the gray value larger than the second segmentation threshold are suspected defect areas.
4. The method for identifying the defects of the composite film according to claim 1, wherein the method for obtaining the gray scale deviation index specifically comprises the following steps:
wherein,
is shown as
The gray scale deviation index corresponding to each pixel point,
the gray value of the z-th pixel point is represented,
representing the gray value of the first other pixel in the window where the z-th pixel is located,
representing the gray value of the jth pixel point in the window where the jth pixel point is located,
representing the total number of other pixels except the center point within the window, exp () represents an exponential function with a natural constant e as the base.
5. The method for identifying defects of a composite film according to claim 1, wherein the dividing of the pixels into three levels according to the gray scale deviation index specifically comprises: and acquiring a difference value between the gray level deviation indexes of any two pixel points, and dividing all the pixel points into three levels based on all the difference values.
6. The method for identifying the defects of the composite film according to claim 1, wherein the step of determining the possible defect pixel points according to the number of different grades in the window corresponding to the pixel points specifically comprises the following steps:
for a window where any one pixel point is located, if pixel points of three grades exist in all the pixel points in the window, the any one pixel point is a possible defect pixel point; if the pixel points of the three grades do not exist, the window is expanded according to the set step length, if the pixel points of the three grades exist in all the pixel points in the expanded window, any one pixel point is a possible defect area, and if the pixel points of the three grades do not exist in all the pixel points in the expanded window, any one pixel point is a noise pixel point.
7. The method for identifying the defects of the composite film as claimed in claim 1, wherein the determining the connected region according to the non-connectivity index and the index threshold specifically comprises:
when the non-connectivity indexes corresponding to the end points of the possible defect area are all smaller than the index threshold, connecting the possible defect area with the possible defect area corresponding to the non-connectivity index smaller than the index threshold; when the non-connectivity index corresponding to only one end point of the possible defect area is smaller than the index threshold, calculating the shortest distance from the other end point to the edge of the composite film image, if the shortest distance is smaller than the index threshold, connecting the possible defect area with the possible defect area corresponding to the non-connectivity index smaller than the index threshold, and if the shortest distance is greater than or equal to the index threshold, removing the possible defect area without connection; when the non-connectivity indexes corresponding to the end points of the possible defect areas are not less than the index threshold, the possible defect areas are discarded and are not connected; all connected regions constitute connected regions.
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