CN111739012A - Camera module white spot detecting system based on turntable - Google Patents
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Abstract
The invention relates to the technical field of image processing, in particular to a camera module white spot detection system based on a turntable, which comprises an acquisition module, a processing module and a control module, wherein the acquisition module is used for acquiring an image to be detected, which is shot by a camera module; the seed module is used for generating a seed region according to the pixel points with the gray values larger than the first threshold value in the image to be detected; the expanding module is used for carrying out region expansion by taking the seed region as a center to obtain an expanded region image; the target module is used for obtaining a target area according to the pixel points with the gray values larger than the second threshold value in the image of the expansion area; and the detection module is used for calculating the overall average brightness value of the image to be detected, analyzing whether the area average brightness value in the target area is higher than the overall average brightness value or not, and judging whether the surface of the lens has white spots or not according to the analysis result. The invention solves the technical problem that in the prior art, under the condition that the background gray value is uneven when the lens is imaged, the dirty area of the lens is difficult to accurately detect so as to determine the white spot.
Description
Technical Field
The invention relates to the technical field of image processing, in particular to a camera module white spot detection system based on a turntable.
Background
After the camera is manufactured, due to the problem of lens parameter setting or pollution, white spots may exist on the image output by the camera, thereby affecting the image quality. Therefore, it is necessary to analyze the image, determine the exudate region, and detect the size of the exudate region to determine whether the camera meets the requirements.
At present, in order to ensure that the surface of a lens of a camera module has strict, clean and pollution-free quality requirements, the surface of the lens is detected. However, the human eye identification has strong subjectivity, and the dirt condition is difficult to reflect objectively. In view of the above, document CN106851264A discloses a method for detecting a lens surface of a camera module, which includes the following steps: acquiring an imaging picture of the camera module; calculating the integral average brightness value of the imaging picture; dividing the imaging picture into a plurality of groups; scanning each group by using a preset frame, and analyzing whether the brightness of a region consisting of a plurality of continuous pixel points in the group is lower than the overall average brightness value; and judging whether the surface of the lens is dirty or not according to the scanning analysis result. According to the scheme, whether the surface of the lens of the camera module is dirty or not can be automatically judged, the detection efficiency is high, the dirty condition can be accurately reflected, manual visual identification is not needed, and the labor cost is low.
In the production and assembly process of the lens, due to the limitation of objective environmental factors, such as clothes and hair of workers, various foreign matters are inevitably dropped on the lens, such as dust, so that the lens is imaged to generate shadows, such as white spots, when in use. Although the dirt detection is an important evaluation item in the lens production and use process, the surface of the lens of the camera module can be efficiently detected. However, in practice, the lens often has a problem of uneven background gray scale value during imaging, and in such a case, it is difficult for the prior art to accurately detect the dirty area of the lens.
Disclosure of Invention
The invention provides a camera module white spot detection system based on a turntable, which solves the technical problem that in the prior art, a dirty area of a lens is difficult to accurately detect under the condition that a background gray value is uneven when the lens is imaged, so that a white spot is determined.
The basic scheme provided by the invention is as follows: camera module white spot detecting system based on carousel includes:
the acquisition module is used for acquiring an image to be detected shot by the camera module;
the seed module is used for generating a seed region according to the pixel points with the gray values larger than the first threshold value in the image to be detected;
the expanding module is used for carrying out region expansion by taking the seed region as a center to obtain an expanded region image;
the target module is used for obtaining a target area according to the pixel points with the gray values larger than the second threshold value in the image of the expansion area;
and the detection module is used for calculating the overall average brightness value of the image to be detected, analyzing whether the area average brightness value in the target area is higher than the overall average brightness value or not, and judging whether the surface of the lens has white spots or not according to the analysis result.
The working principle and the advantages of the invention are as follows: when foreign matters are attached to the lens, certain dirt causes shadow of an image shot by the lens. When an image has an exudate, an image region corresponding to the contamination is usually bright, the gray value is high, and a pixel point with the gray value higher than the average gray value of a local neighborhood block can be identified by a self-adaptive local threshold segmentation method, so that the determination of the contamination region and the detection of the exudate are facilitated. In addition, after the seed region is preliminarily determined, the target region is obtained by determining the expansion region and increasing the local threshold (changing the local threshold from the first threshold to a larger second threshold) to perform adaptive local threshold segmentation, so that local bright pixels with gray values close to the average gray value of the local neighborhood block in the expansion region are also listed as pixels in the target region, and therefore, a faint white spot region with a small gray value difference from the background gray value can be obtained after the region is increased. Therefore, the whole target region can be completely and accurately obtained by the scheme, and a more accurate lens white spot detection result is obtained.
The invention solves the technical problem that in the prior art, under the condition that the background gray value is uneven when the lens is imaged, the dirty area of the lens is difficult to accurately detect so as to determine the white spot.
Further, a first threshold corresponding to each pixel point in the image to be detected is larger than the average gray value of the local area where the pixel point is located.
Has the advantages that: the first threshold corresponding to each pixel point is larger than the average gray value of the local area where the pixel point is located, and the pixel points with smaller gray values can be excluded.
Further, a second threshold corresponding to each pixel point in the expanded region image is larger than the first threshold and smaller than or equal to the average gray value of the local region where the pixel point is located.
Has the advantages that: the second threshold corresponding to each pixel point is larger than the first threshold, so that the pixel points can be further screened; and the average gray value of the local area where the pixel point is located is less than or equal to the average gray value of the local area where the pixel point is located, so that the expansion of the area is facilitated.
Further, the first threshold corresponding to each pixel point is equal to the average gray value of the local area where each pixel point is located plus a preset value.
Has the advantages that: the first threshold is equal to the average gray value of the local area where each pixel point is located plus a preset value, so that the first threshold can be conveniently adjusted by setting the preset value.
Further, the target module further comprises an updating unit for obtaining an updated target area.
Has the advantages that: and the obtained target area is updated, so that the error of the target area is favorably corrected.
Further, the detection module further comprises: the acquisition unit is used for acquiring the brightness value of any pixel point in the target area; and the eliminating unit is used for comparing the brightness value of the pixel point with the overall average brightness value and eliminating the pixel point with the brightness value smaller than the overall average brightness value.
Has the advantages that: the pixel point with the brightness value smaller than the integral average brightness value is rejected by comparing the pixel point brightness value with the integral average brightness value, so that the error of judging whether the white spots exist is reduced.
Further, the detection module also comprises a probability unit used for obtaining the prediction probability of whether the camera has the white spot; and when the prediction probability is greater than the probability threshold value, judging that the camera has the white spot.
Has the advantages that: the result of detecting the white spots is determined in a probability form, which is favorable for quantifying the result of detection.
Furthermore, the acquisition module also comprises a filtering unit used for reducing noise of the image to be detected.
Has the advantages that: the method is favorable for reducing the interference of environmental factors to the image.
Furthermore, the acquisition module also comprises a defogging unit which is used for defogging the image to be detected.
Has the advantages that: the method is favorable for improving the definition of the image to be detected.
Furthermore, the acquisition module also comprises an equalization unit which is used for equalizing the image to be detected.
Has the advantages that: the contrast of the image to be detected can be enhanced.
Drawings
Fig. 1 is a system structure block diagram of an embodiment of a camera module white spot detection system based on a turntable.
Detailed Description
The following is further detailed by the specific embodiments:
example 1
The embodiment of the camera module white spot detection system based on the turntable is basically as shown in the attached figure 1, and comprises the following components: the acquisition module is used for acquiring an image to be detected shot by the camera module; the seed module is used for generating a seed region according to the pixel points with the gray values larger than the first threshold value in the image to be detected; the expanding module is used for carrying out region expansion by taking the seed region as a center to obtain an expanded region image; the target module is used for obtaining a target area according to the pixel points with the gray values larger than the second threshold value in the image of the expansion area; and the detection module is used for calculating the overall average brightness value of the image to be detected, analyzing whether the area average brightness value in the target area is higher than the overall average brightness value or not, and judging whether the surface of the lens has white spots or not according to the analysis result.
The camera obtains an image to be detected by shooting a template of a white background, wherein the template of the white background can be a white board, white paper, white cloth and the like. After the camera shoots an image to be detected, the acquisition module is used for acquiring the image to be detected and further comprises a filtering unit, a defogging unit and a balancing unit. After the image to be detected is acquired, the image to be detected needs to be preprocessed. In order to reduce the interference of environmental factors to the image to be detected, the filtering unit performs noise reduction on the image to be detected, and specifically adopts a Gaussian filtering method. In order to improve the definition of the image to be detected, the defogging unit performs defogging processing on the image to be detected, and specifically adopts a real-time defogging algorithm based on mean value filtering. In order to enhance the contrast of the image to be detected, the equalization unit performs equalization processing on the image to be detected, and specifically, an adaptive histogram equalization algorithm is adopted.
And then, the seed module generates a seed region according to the pixel points of which the gray values are greater than the first threshold value in the image to be detected. In order to exclude the pixel points with smaller gray values, the first threshold corresponding to each pixel point in the image to be detected is larger than the average gray value of the local area where the pixel point is located. In addition, in order to adjust the first threshold, the first threshold corresponding to each pixel point is equal to the average gray value of the local area where each pixel point is located plus a preset value. Specifically, in the first step, a corresponding local neighborhood is determined for each pixel point in the image to be detected, and the local neighborhood corresponding to each pixel point is a rectangle or a circle with the pixel point as the center. For example, the local neighborhood is a rectangle, the preset neighborhood extension size is nPixel, which is 20 pixels in this embodiment, and the Pixel point a is any one Pixel point in the image to be detected, and then 20 pixels are respectively extended from the upper, lower, left, and right directions by taking the Pixel point a as a center, so as to obtain a local neighborhood block where the Pixel point a is located, where the local neighborhood block size is (2n +1) × (2n +1) Pixel. And secondly, determining a first threshold corresponding to each pixel point according to the average gray value of the local neighborhood where each pixel point is located. In this embodiment, for a single pixel, after obtaining an average gray value of a local area where the pixel is located, a preset value x is added to the average gray value to obtain a first threshold, where the preset value x is not 0 and may be set manually. For example, if the average gray value of the local neighborhood where the pixel point a is located is u, the first threshold corresponding to the pixel point a is u + x. Because the local neighborhoods of the pixel points are different, the first threshold corresponding to each pixel point may be different. And thirdly, determining pixel points with gray values larger than a first threshold value in the image to be detected to form a seed region in the image to be detected, wherein the seed region is a region with larger difference with the local background gray values.
And then, the target module obtains a target area according to the pixel points with the gray values larger than the second threshold value in the image of the expansion area. Specifically, according to the size of a preset dirty area, the area is expanded with the seed area as the center. Typically, the predetermined soil size is obtained from experimental tests. For example, the size of the dirt area measured by an experiment does not exceed 220 pixels, the preset size of the dirt area is set to 220 pixels, and an area image with an image size close to or equal to 220 pixels is obtained by expanding the area image with the seed area as the center and is used as an expanded area image.
And then, the target module obtains a target area according to the pixel points with the gray values larger than the second threshold value in the image of the expansion area. In order to correct the error of the target area, the target module further comprises an updating unit for obtaining an updated target area. In order to further screen the pixel points and facilitate the expansion of the region, the second threshold corresponding to each pixel point in the expanded region image is larger than the first threshold and is smaller than or equal to the average gray value of the local region where the pixel point is located. Specifically, in the first step, the seed area is used as the initial area to be soiled. And secondly, adding the preset value to a preset stepping value to obtain an updated preset value, adding the updated preset value to the average gray value of the local neighborhood where each pixel point is located in the expanded region to obtain a second threshold value of each pixel point, and obtaining an updated to-be-polluted region according to the pixel points with the gray values larger than the second threshold value in the image of the expanded region. And thirdly, if the area growth rate of the updated to-be-determined dirty area relative to the historical to-be-determined dirty area is greater than a growth threshold, determining that the to-be-determined dirty area is a non-dirty area, and if not, performing the fourth step. And step four, if the second threshold value of each pixel point is equal to the average gray level of the local neighborhood where the pixel point is located, the step five is carried out, and if not, the step two is carried out. Fifthly, if the updated size of the area to be determined is larger than the preset dirt size, determining that the area to be determined is a non-dirt area; and otherwise, taking the updated pending dirty area as the target area after the area growth.
And finally, the detection module calculates the overall average brightness value of the image to be detected, analyzes whether the area average brightness value in the target area is higher than the overall average brightness value or not, and judges whether the white spot exists on the surface of the lens or not according to the analysis result. For example, if the average brightness value of the region in the target region is 240 and the overall average brightness value is 235, the average brightness value of the region in the target region is higher than the overall average brightness value, and it is determined that a white spot exists on the surface of the lens.
Example 2
The only difference from embodiment 1 is that,
in order to reduce the error when judging whether the white spots exist, the detection module also comprises an acquisition unit for acquiring the brightness value of any pixel point in the target area; and the eliminating unit is used for comparing the brightness value of the pixel point with the overall average brightness value and eliminating the pixel point with the brightness value smaller than the overall average brightness value. For example, the brightness value of the pixel B in the target region is 198, the overall average brightness value is 200, and the brightness value of the pixel B is smaller than the overall average brightness value, and should be eliminated.
In addition, in order to quantify the detection result, the detection module further comprises a probability unit for obtaining the prediction probability of whether the camera has the white spot, and when the prediction probability is larger than a probability threshold value, the camera is judged to have the white spot. For example, a functional relation between the probability of the camera having the white spot and the average brightness value of the region in the target region is established according to the past empirical data, and a least square method can be specifically adopted. And if the probability threshold is 80 percent and the prediction probability is 85 percent and the prediction probability is greater than the probability threshold, judging that the white spot exists in the camera.
Example 3
The difference from embodiment 2 is that in this embodiment, the device further includes a shot object and a cleaning structure, a reference point F is artificially marked on the shot object, an LED lamp is fixed at the reference point F, and the cleaning mechanism blows airflow to clean the shot object and remove dust, hair and the like on the surface.
When the camera takes a picture of the shot, the picture is displayed on the display screen, and the position of the reference point F is F1. Next, the position of the reference point F on the photographic subject is moved to a point G, which is at a position G1 on the display screen. The position of the reference point F on the photographic subject is moved so that the point of the reference point F on the display screen is located exactly on the edge of the display screen. And then, establishing a rectangular coordinate system on the display screen by taking the F1 as an origin to determine the coordinate of each pixel point of the shot picture on the display screen, overlapping the shot picture with a completely qualified picture prepared in advance, and comparing the brightness of each pixel point to determine the coordinate of the pixel point with higher brightness value on the shot picture, such as (6, 8). Judging whether the deviation area of the pixel point is larger than a preset area: if the area is larger than the preset area, the camera needs to be cleaned; if the area is smaller than the preset area, the camera is qualified. For example, the preset area is a circle with a radius of 0.5cm, if the deviation area of the pixel point is a circle, the circle center is at (6, 8), the radius is 1cm, and the circle center is larger than the preset area, which indicates that the camera needs to be cleaned; otherwise, if the radius is 0.4cm and is smaller than the preset area, the camera is qualified.
The foregoing is merely an example of the present invention, and common general knowledge in the field of known specific structures and characteristics is not described herein in any greater extent than that known in the art at the filing date or prior to the priority date of the application, so that those skilled in the art can now appreciate that all of the above-described techniques in this field and have the ability to apply routine experimentation before this date can be combined with one or more of the present teachings to complete and implement the present invention, and that certain typical known structures or known methods do not pose any impediments to the implementation of the present invention by those skilled in the art. It should be noted that, for those skilled in the art, without departing from the structure of the present invention, several changes and modifications can be made, which should also be regarded as the protection scope of the present invention, and these will not affect the effect of the implementation of the present invention and the practicability of the patent. The scope of the claims of the present application shall be determined by the contents of the claims, and the description of the embodiments and the like in the specification shall be used to explain the contents of the claims.
Claims (10)
1. Camera module white spot detecting system based on carousel, its characterized in that includes:
the acquisition module is used for acquiring an image to be detected shot by the camera module;
the seed module is used for generating a seed region according to the pixel points with the gray values larger than the first threshold value in the image to be detected;
the expanding module is used for carrying out region expansion by taking the seed region as a center to obtain an expanded region image;
the target module is used for obtaining a target area according to the pixel points with the gray values larger than the second threshold value in the image of the expansion area;
and the detection module is used for calculating the overall average brightness value of the image to be detected, analyzing whether the area average brightness value in the target area is higher than the overall average brightness value or not, and judging whether the surface of the lens has white spots or not according to the analysis result.
2. The turntable-based camera module exudate detection system of claim 1, wherein: and the first threshold corresponding to each pixel point in the image to be detected is larger than the average gray value of the local area where the pixel point is located.
3. The turntable-based camera module exudate detection system of claim 2, wherein: and the second threshold corresponding to each pixel point in the expansion area image is larger than the first threshold and is smaller than or equal to the average gray value of the local area where the pixel point is located.
4. The turntable-based camera module exudate detection system of claim 3, wherein: and the first threshold corresponding to each pixel point is equal to the average gray value of the local area where each pixel point is located plus a preset value.
5. The turntable-based camera module exudate detection system of claim 1, wherein: the target module further comprises an updating unit for obtaining an updated target area.
6. The turntable-based camera module exudate detection system of claim 5, wherein: the detection module further comprises: the acquisition unit is used for acquiring the brightness value of any pixel point in the target area; and the eliminating unit is used for comparing the brightness value of the pixel point with the overall average brightness value and eliminating the pixel point with the brightness value smaller than the overall average brightness value.
7. The turntable-based camera module exudate detection system of claim 6, wherein: the detection module also comprises a probability unit used for obtaining the prediction probability of whether the camera has the white spot or not; and when the prediction probability is greater than the probability threshold value, judging that the camera has the white spot.
8. The turntable-based camera module exudate detection system of claim 1, wherein: the acquisition module also comprises a filtering unit used for reducing noise of the image to be detected.
9. The turntable-based camera module exudate detection system of claim 1, wherein: the acquisition module also comprises a defogging unit which is used for defogging the image to be detected.
10. The turntable-based camera module exudate detection system of claim 1, wherein: the acquisition module also comprises an equalization unit which is used for equalizing the image to be detected.
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