A detection and interception method and device for camera module peripheral shallow stripe defects

Abstract

The application discloses a kind of detection interception methods for the peripheral shallow stripe defect of camera module, comprising: obtaining the center overexposure image of camera module;At least one side periphery of the center overexposure image is cut, and at least one peripheral image is obtained;Each column of pixel points in each peripheral image is filtered using edge detection filter, and a plurality of column pixel filter values are obtained;Each column of pixel filter values in the same peripheral image is accumulated, and at least one filter accumulation value is obtained;Each filter accumulation value is compared with a predetermined threshold value respectively to determine whether the camera module has peripheral shallow stripe defect.The detection interception method is aimed at detecting and intercepting the peripheral shallow stripe defect of camera module in production stage, so as to avoid the camera module with peripheral shallow stripe defect from flowing to the market.The application also discloses a kind of detection interception devices for realizing the above-mentioned detection interception method.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of camera module detection, and in particular to a camera module peripheral shallow stripe defect detection and interception method and device. BACKGROUND

[0002] A camera module is a modular component that integrates an image sensor, an optical lens, an image processing chip, and other related circuits. This modular design makes the integration of cameras much simpler and can easily be integrated into various devices such as smartphones, tablets, smart home devices, and industrial vision systems.

[0003] The working principle of a camera module is that the light of the photographed object is projected onto the image sensor through the lens to generate an optical image. The optical signal is converted into an electrical signal by a photodiode, and then the obtained analog signal is converted into a digital signal by an analog-to-digital converter (ADC). After the signal is preliminarily processed, the data is processed by an ISP and finally converted into an image that can be read on the screen.

[0004] When the resistance of some column pixels of the image sensor deviates abnormally, causing a large deviation in signal voltage, or when there is a large deviation in the threshold voltage of some analog-to-digital converters (ADCs), shallow stripes will appear in the peripheral area of the camera module output image. In order to reduce the stripes generated during the operation of the column-type AD converter, a solid-state camera device is disclosed in Chinese patent CN201410072518.6, which has a pixel array portion configured with pixels that accumulate electric charges after photoelectric conversion; a reference voltage generation circuit that generates a reference voltage; a column ADC circuit that is provided with a comparator that compares the pixel signal read from the pixel with the reference voltage, and calculates the AD conversion value of the pixel signal based on the comparison result of the comparator; a vertical signal line that transmits the pixel signal according to each column; a capacitor that performs analog sampling by retaining the charge corresponding to the pixel signal according to each column; an inter-column short circuit circuit that shorts the vertical signal line between columns before analog sampling; and an analog sampling time control unit that controls the time from the release of the inter-column short circuit to the start of analog sampling.

[0005] However, improving the peripheral shallow stripe defect of the camera by optimizing the circuit is not only technically complex, but also requires more research and development resources in the design stage, including circuit design, simulation, testing, and other aspects, and has a relatively high technical threshold. In addition, the optimization circuit requires more complex circuit structures and higher-level components, thereby increasing production costs. Although the optimization circuit scheme aims to fundamentally reduce the stripe problem, its actual effect may be affected by various factors, such as process fluctuations in the production process and component performance differences, which may introduce new deviation problems. SUMMARY

[0006] To solve the above problems of the prior art, the present application provides a detection and interception method and device for peripheral shallow stripe defects of a camera module, which aims to detect and intercept peripheral shallow stripe defects of a camera module in the production stage, thereby avoiding the flow of camera modules with peripheral shallow stripe defects to the market.

[0007] The technical problem to be solved by the present application is solved by the following technical scheme:

[0008] A detection and interception method for peripheral shallow stripe defects of a camera module, comprising the following steps:

[0009] Step 100: obtaining a center overexposure image of a camera module;

[0010] Step 200: cropping at least one side of the center overexposure image to obtain at least one peripheral image;

[0011] Step 300: using an edge detection filter to filter each column of pixel points in each peripheral image to obtain a plurality of column pixel filter values;

[0012] Step 400: adding each column pixel filter value of the same peripheral image to obtain at least one filter accumulation value;

[0013] Step 500: comparing each filter accumulation value with a preset threshold to determine whether the camera module has a peripheral shallow stripe defect.

[0014] Further, in step 100, the steps of obtaining a center overexposure image of a camera module are as follows:

[0015] Step 110: setting the exposure time of the camera module and the brightness value of the light source panel to make the center area of the camera module normally exposed;

[0016] Step 120: increasing the gain value of the camera module to cause overexposure in the center area of the camera module;

[0017] Step 130: control the camera module to capture the light source panel to obtain an original image;

[0018] Step 140: if the number of original images is only one, the original image is taken as the center overexposure image; if the number of original images is more than one, each original image is superimposed to obtain the center overexposure image.

[0019] Further, the camera module has multiple color channels; in step 120, only the gain value of the camera module in a single color channel is increased, and in step 300, only the pixels in each column of each peripheral image are filtered in a single color channel, and the color channel of the increased gain value and the filtering processing is the same.

[0020] Further, the single color channel is a red channel.

[0021] Further, the center overexposure image has a four-side periphery; in step 200, when the center overexposure image is cropped, the four-side periphery of the center overexposure image is cropped at the same time, or according to the past detection results of the same batch of camera modules or the same model camera modules, only one side or two sides of the periphery of the center overexposure image is cropped.

[0022] Further, the cropping size of each peripheral image is pre-set or automatically generated by an algorithm.

[0023] Further, when the cropping size of each peripheral image is automatically generated by an algorithm, first, the brightness value of all pixels in the center overexposure image is obtained, then whether each pixel is overexposed is judged according to the brightness value, and each overexposed pixel is extracted to form the center region, and each normally exposed pixel is extracted to form the peripheral region, and finally, the cropping size of each peripheral image is generated according to the length and width size of the peripheral region and the preset reduction ratio.

[0024] Further, in step 300, before filtering each column of pixels in each peripheral image, edge enhancement processing is performed on each peripheral image.

[0025] Further, in step 500, when one of the filter accumulation values is equal to or greater than the preset threshold value, it is determined that the camera module has peripheral shallow stripes, and when each filter accumulation value is less than the preset threshold value, it is determined that the camera module does not have peripheral shallow stripes.

[0026] The application discloses a detection and interception device for a camera module peripheral shallow stripe defect, which comprises a processor and a memory electrically connected with the processor, the memory stores a computer program for the processor, and the processor performs the detection and interception method when executing the computer program.

[0027] The application has the following beneficial effects: the detection and interception method of the application improves the contrast between the shallow stripe and the pixel points in the peripheral region by overexposure processing on the center region of the camera module, thereby obtaining the center overexposure image, then performing cutting and edge detection filtering on the center overexposure image in sequence, and determining whether the camera module has the peripheral shallow stripe defect according to the filtering cumulative value, so that the peripheral shallow stripe defect of the camera module can be detected and intercepted in the production stage, thereby avoiding the camera module with the peripheral shallow stripe defect from flowing into the market. BRIEF DESCRIPTION OF DRAWINGS

[0028] Figure 1 The application provides a step block diagram of the detection and interception method.

[0029] Figure 2 The application provides a region schematic view of the center overexposure image of the detection and interception method.

[0030] Figure 3 The application provides a cutting schematic view of the center overexposure image of the detection and interception method.

[0031] Figure 4 The application provides another cutting schematic view of the center overexposure image of the detection and interception method.

[0032] Figure 5 The application provides still another cutting schematic view of the center overexposure image of the detection and interception method.

[0033] Figure 6 The application provides a step block diagram of step 100 of the detection and interception method.

[0034] Figure 7 The application provides a principle block diagram of the detection and interception device. DETAILED DESCRIPTION

[0035] The application will be described in detail below with reference to the drawings and embodiments, wherein the same or similar reference numerals represent the same or similar elements or elements with the same or similar functions throughout the drawings. The embodiments described below with reference to the drawings are exemplary and are intended to explain the application, and cannot be understood as a limitation of the application.

[0036] In the description of the present application, it is to be understood by the terms "length", "width", "upper", "lower", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer" and the like indicate the orientation or positional relationship shown in the drawings, which are only for the convenience of describing the present application and simplifying the description, and do not indicate or imply that the devices or elements referred to must have a particular orientation, be constructed and operated in a particular orientation, and therefore cannot be understood as limiting the present application.

[0037] In addition, the terms "first", "second", "third" are only for descriptive purposes and cannot be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Therefore, the features defined with "first", "second", "third" can explicitly or implicitly include one or more of the features. In the description of the present application, the meaning of "multiple" is two or more, unless otherwise specifically limited.

[0038] In the present application, unless otherwise specifically defined and limited, the terms "mounting", "connection", "connection", "fixing", "setting" and the like should be broadly understood, for example, it can be fixedly connected, or it can be detachably connected, or it can be integrated; it can be mechanically connected, or it can be electrically connected; it can be directly connected, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two elements or the interaction relationship between two elements. For those skilled in the art, the specific meaning of the above terms in the present application can be understood according to the specific circumstances.

[0039] Embodiment one

[0040] As shown in Figure 1 A detection and interception method for camera module peripheral shallow stripe defects, comprising the following steps:

[0041] Step 100: Obtain the center overexposure image of the camera module.

[0042] In this step 100, as Figure 2 Described, the image output by the camera module includes a center region and a peripheral region, and the peripheral region surrounds the center region. When the wire resistance of some column pixels in the image sensor of the camera module is abnormally deviated, thereby causing a large deviation of the signal voltage, or the threshold voltage of some analog-to-digital converters (ADCs) in the camera module has a large deviation, the peripheral region of the image output by the camera module will appear a shallow stripe.

[0043] The term "center overexposed image" refers to an image where the central region is overexposed, while the peripheral region is normally exposed. The central and peripheral regions are defined based on the brightness distribution of pixels. Due to the focusing effect of optical lenses, pixels closer to the geometric center of the image are brighter, and pixels farther from the geometric center are dimmer. There is no clear boundary between the central and peripheral regions. Therefore, this patent defines the set of overexposed pixels near the geometric center of the image in the center overexposed image as the central region, and the set of normally exposed pixels far from the geometric center of the image in the center overexposed image as the peripheral region.

[0044] The reason for overexposing the central area is that the light stripes have low brightness. When the central area is normally exposed, the brightness of the outer area is too low, and the brightness difference between the pixels of the light stripes and the outer area is small. However, when the central area is overexposed, the brightness of the outer area is higher, and the brightness difference between the pixels of the light stripes and the outer area is larger. This can improve the contrast between the pixels of the light stripes and the outer area, making it easier to perform edge detection of the light stripes in the outer area.

[0045] Step 200: Crop at least one outer edge of the overexposed central image to obtain at least one outer edge image.

[0046] In step 200, the overexposed central image has four outer peripheries, located on the upper, lower, left, and right sides of the central region, respectively. For ease of explanation, this embodiment defines the four outer peripheries of the overexposed central image as the upper periphery, lower periphery, left periphery, and right periphery, respectively. The upper periphery, lower periphery, left periphery, and right periphery are connected end to end in sequence to form a periphery surrounding the central region.

[0047] When cropping the overexposed image in the center, such as Figure 3 The method can simultaneously crop the four outer edges of the central overexposed image to simultaneously obtain the upper outer edge image, lower outer edge image, left outer edge image, and right outer edge image of the central overexposed image. Subsequently, these four outer edge images can be detected separately to determine whether there are shallow stripes.

[0048] Of course, in order to improve detection efficiency, based on past detection results of the same batch of camera modules or the same model of camera modules, only one or both outer edges of the central overexposed image can be cropped to obtain one or two outer images for detection to determine whether shallow stripes exist.

[0049] For example, such as Figure 4As shown in FIG. 1, in the past detection results of a batch of camera modules or a model of camera modules, the shallow stripes all appear on the left periphery, so when detecting the batch of camera modules or the model of camera modules, only the left periphery of the center overexposure image can be cropped to obtain a left periphery image for detection to determine whether the shallow stripes exist; for example, as shown in FIG. 2, in the past detection results of a batch of camera modules or a model of camera modules, the shallow stripes all appear on the right periphery, so when detecting the batch of camera modules or the model of camera modules, only the right periphery of the center overexposure image can be cropped to obtain a right periphery image for detection to determine whether the shallow stripes exist. Figure 5 As shown in FIG. 1, in the past detection results of a batch of camera modules or a model of camera modules, the shallow stripes all appear on the left periphery, so when detecting the batch of camera modules or the model of camera modules, only the left periphery of the center overexposure image can be cropped to obtain a left periphery image for detection to determine whether the shallow stripes exist; for example, as shown in FIG. 2, in the past detection results of a batch of camera modules or a model of camera modules, the shallow stripes all appear on the right periphery, so when detecting the batch of camera modules or the model of camera modules, only the right periphery of the center overexposure image can be cropped to obtain a right periphery image for detection to determine whether the shallow stripes exist.

[0050] The cropping size of each periphery image can be pre-set by the detection personnel according to experience, or can be automatically generated by using an algorithm. When the cropping size of each periphery image is automatically generated by using the algorithm, first, the brightness values of all pixel points in the center overexposure image are obtained, then whether each pixel point is overexposed is judged according to the brightness values, and each overexposed pixel point is extracted to form the center region, and each normally exposed pixel point is extracted to form the periphery region, and finally the cropping size of each periphery image is generated according to the length and width size of the periphery region and the pre-set reduction ratio.

[0051] Step 300: filtering processing is performed on each column of pixel points in each periphery image by using an edge detection filter to obtain a plurality of column pixel filter values.

[0052] In this step 300, the edge detection filter can be but is not limited to a Laplacian filter, a gradient filter, a nonlinear filter or a high-pass filter, etc. One column pixel filter value corresponds to one column of pixel points, and one periphery image has a plurality of column pixel filter values.

[0053] Preferably, before the filtering processing is performed on each column of pixel points in each periphery image, edge enhancement processing is first performed on each periphery image to improve the filtering processing effect of the edge detection filter.

[0054] In this step 300, the edge enhancement processing can be but is not limited to a morphological filtering method, an adaptive filtering method or a histogram equalization method, etc.

[0055] Step 400: each column pixel filter value of the same periphery image is added up to obtain at least one filter accumulation value.

[0056] In step 400, each accumulated filter value corresponds to an outer peripheral image, and the overexposed central image has at least one accumulated filter value. For example, the accumulated filter values ​​of each column of pixels in the upper peripheral image are summed to obtain a first accumulated filter value corresponding to the upper peripheral of the overexposed central image; the accumulated filter values ​​of each column of pixels in the lower peripheral image are summed to obtain a second accumulated filter value corresponding to the lower peripheral of the overexposed central image; the accumulated filter values ​​of each column of pixels in the left peripheral image are summed to obtain a third accumulated filter value corresponding to the left peripheral of the overexposed central image; and the accumulated filter values ​​of each column of pixels in the lower peripheral image are summed to obtain a fourth accumulated filter value corresponding to the lower peripheral of the overexposed central image.

[0057] Step 500: Compare each filtered cumulative value with a preset threshold to determine whether the camera module has peripheral shallow stripe defects.

[0058] In step 500, when one of the filter accumulation values ​​is equal to or greater than the preset threshold, it is determined that the camera module has peripheral shallow stripes; when all filter accumulation values ​​are less than the preset threshold, it is determined that the camera module does not have peripheral shallow stripes.

[0059] The detection and interception method of this patent overexposes the central area of ​​the camera module to improve the contrast between the shallow stripes and the pixels in the peripheral area, thereby obtaining the central overexposed image. Then, the central overexposed image is cropped and edge detection filtered sequentially, and the presence of peripheral shallow stripe defects in the camera module is determined based on the cumulative filter value. Peripheral shallow stripe defects in the camera module can be detected and intercepted during the production stage, thereby preventing camera modules with peripheral shallow stripe defects from entering the market.

[0060] Example 2

[0061] As an optimization of Embodiment 1, in this embodiment, such as Figure 6 As shown, in step 100, the steps for obtaining the center overexposed image of the camera module are as follows:

[0062] Step 110: Set the exposure time of the camera module and the brightness value of the light source panel to ensure that the central area of ​​the camera module is properly exposed.

[0063] In step 110, the light source panel is positioned in front of the lens of the camera module so that the camera module exposes the light source panel. The exposure time of the camera module and the brightness value of the light source panel are set according to the different models of the camera module so that the central area of ​​the camera module is properly exposed and the exposure time of the camera module and the brightness value of the light source panel are avoided from affecting the overexposure control of the camera module.

[0064] Step 120: increase the gain value of the camera module, so that the center region of the camera module appears overexposure.

[0065] In this step 120, the gain value of the camera module can be gradually increased from a preset initial value (generally 0) until the center region of the camera module appears overexposure; or the gain value of the camera module can be directly increased to the gain value of the same batch of camera modules or the same model of camera modules when the center region appears overexposure in the past detection.

[0066] Due to the light condensing effect of the optical lens, the closer the pixel point is to the image geometric center, the larger the brightness is, and the farther the pixel point is from the image geometric center, the smaller the brightness is. With the increase of the gain value of the camera module, the brightness value of the pixel point close to the image geometric center will first reach 255. When the proportion of the pixel points with brightness value reaching 255 in the entire image reaches a preset range (generally 10%-20%), it can be determined that the center region of the camera module appears overexposure.

[0067] Step 130: control the camera module to shoot the light source panel to obtain an original image.

[0068] In this step 130, each pixel point with overexposure (brightness value reaching 255) in the original image forms the center region together, and each pixel point with normal exposure (brightness value lower than 255) forms the peripheral region together.

[0069] Step 140: if the number of original images is only one, the original image is taken as the center overexposure image; if the number of original images is more than one, each original image is superimposed and synthesized to obtain the center overexposure image.

[0070] In this step 140, if the original image shot by the camera module has only one, the original image is directly taken as the center overexposure image for detection; if the original image shot by the camera module has more than one, each original image is superimposed and synthesized, and the synthesized image is taken as the center overexposure image for detection. By superimposing and synthesizing multiple original images to obtain the center overexposure image, it can prevent the influence on the detection result caused by the noise points in a single original image, and improve the detection accuracy.

[0071] Example Three

[0072] As an optimization scheme of embodiment two, in the present embodiment, the camera module has multiple color channels; in step 120, only the gain value of the camera module on a single color channel is increased, and in step 300, only the pixels in each column of each peripheral image are filtered on a single color channel, and the color channel on which the gain value is increased and the filtering processing are the same.

[0073] Since the sensitivities of different color channels in the camera module to light are different, by only increasing the gain value of the camera module on a single color channel, the present embodiment can avoid the influence of the sensitivities of different color channels on the exposure degree due to the different sensitivities of different color channels.

[0074] It should be noted that when determining whether the center region of the camera module is overexposed in step 120, the overall brightness value of each color channel of the pixel is still used as the basis for judgment, rather than the channel brightness value of a single color channel.

[0075] Each pixel in the image sensor of the camera module is composed of four color channels of RGGB, and the output image format is RAW format. After RAW interpolation conversion, the image format of the center overexposure image is RGB format, that is, each pixel of the center overexposure image has three color channels of RGB, among which the G channel (i.e. the green channel) has the highest sensitivity to light, and the R channel (i.e. the red channel) has the lowest sensitivity to light. Therefore, under the same exposure time and light source brightness, the G channel of the center overexposure image is the brightest, and the R channel is the darkest. By increasing the gain value of the R channel to make the center region of the camera module overexposed, the contrast between the shallow stripes and the pixels in the peripheral region can be maximized.

[0076] Embodiment four

[0077] As shown in Figure 7 A detection and interception device for camera module peripheral shallow stripe defects, comprising a processor and a memory electrically connected to the processor, the memory storing a computer program for execution by the processor; when the processor executes the computer program, it performs the detection and interception method of embodiment one, embodiment two or embodiment three.

[0078] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the embodiments of the present application, but not to limit them. Although the embodiments of the present application have been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the embodiments of the present application can still be modified or replaced by equivalents, and these modifications or replacements cannot make the modified technical solutions deviate from the scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for detecting and intercepting a camera module peripheral shallow stripe defect, characterized in that, The method comprises the following steps: Step 100: obtaining a center overexposure image of a camera module; Step 200: cutting at least one side periphery of the center overexposure image to obtain at least one peripheral image; Step 300: filtering each column of pixel points in each peripheral image by using an edge detection filter to obtain a plurality of column pixel filter values; Step 400: accumulating each column pixel filter value of the same peripheral image to obtain at least one filter accumulation value; Step 500: comparing each filter accumulation value with a preset threshold value to determine whether the camera module has peripheral shallow stripe defects.

2. The detection interception method according to claim 1, characterized in that, In step 100, the steps of obtaining the center overexposure image of the camera module are as follows: Step 110: setting the exposure time of the camera module and the brightness value of the light source panel, so that the center area of the camera module is normally exposed; Step 120: increasing the gain value of the camera module, so that the center area of the camera module is overexposed; Step 130: controlling the camera module to capture the light source panel to obtain an original image; Step 140: if the number of original images is only one, the original image is taken as the center overexposure image; if the number of original images is more than one, each original image is superimposed and combined to obtain the center overexposure image.

3. The detection interception method according to claim 2, characterized in that, The camera module has a plurality of color channels; in step 120, only the gain value of the camera module in a single color channel is increased; in step 300, only the column pixel points in each peripheral image are filtered in a single color channel; and the color channel of the increased gain value and the filtering process is the same.

4. The detection interception method according to claim 3, characterized in that, The single color channel is a red channel.

5. The detection interception method of claim 1, wherein, The center overexposure image has four peripheral sides; in step 200, when the center overexposure image is cut, the four peripheral sides of the center overexposure image are cut at the same time, or according to the past detection results of the same batch of camera modules or the same model of camera modules, only one side or two sides of the center overexposure image are cut.

6. The detection interception method according to claim 5, characterized in that, The cutting size of each peripheral image is pre-set or automatically generated by using an algorithm.

7. The detection interception method according to claim 6, characterized in that, When the cutting size of each peripheral image is automatically generated by using an algorithm, first, the brightness values of all pixel points in the center overexposure image are obtained, then it is judged whether each pixel point is overexposed according to the brightness values, and each overexposed pixel point is extracted to form a center area, each normally exposed pixel point is extracted to form a peripheral area, and finally the cutting size of each peripheral image is generated according to the length and width size of the peripheral area and a preset reduction ratio.

8. The detection interception method of claim 1, wherein, In step 300, before filtering each column of pixel points in each peripheral image, each peripheral image is subjected to edge enhancement processing.

9. The detection interception method of claim 1, wherein, In step 500, when one of the filter accumulation values is equal to or greater than the preset threshold value, it is determined that the camera module has peripheral shallow stripes; when each filter accumulation value is less than the preset threshold value, it is determined that the camera module does not have peripheral shallow stripes. 10.A device for detecting and intercepting camera module peripheral shallow stripe defects, comprising a processor and a memory electrically connected to the processor, wherein the memory stores a computer program for the processor to execute, and the device is characterized in that, The processor executes the computer program to perform the detection and interception method of claim 1.

Images