CN109357687B - Defect detection method of CMOS image sensor - Google Patents
Defect detection method of CMOS image sensor Download PDFInfo
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- CN109357687B CN109357687B CN201811044220.9A CN201811044220A CN109357687B CN 109357687 B CN109357687 B CN 109357687B CN 201811044220 A CN201811044220 A CN 201811044220A CN 109357687 B CN109357687 B CN 109357687B
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Abstract
The invention discloses a defect detection method of a CMOS image sensor, which comprises the following steps: collecting a gray card image by using an industrial camera containing a CMOS image sensor; preprocessing a gray card image to obtain a gray scale image; carrying out data shift processing on each pixel value in the gray-scale image to obtain a low-order image; averaging all pixel values in the low-order image to obtain an image mean value; respectively carrying out absolute value calculation on each pixel value in the low-order image and the image mean value to obtain a difference image; calculating the standard deviation of each pixel value in the difference image; and when the obtained standard deviation is larger than a preset standard deviation threshold value, judging that the CMOS image sensor chip has the defect that the bottom noise of the low-order image exceeds the standard. The invention can well meet the test requirement on the high-precision image sensor.
Description
Technical Field
The invention relates to the technical field of semiconductor testing, in particular to a method for detecting defects of a CMOS image sensor for machine vision.
Background
In recent years, CMOS image sensors have been widely used in the digital image field due to their low power consumption, fast speed, high interference rejection and high integration. Gradually, CMOS image sensors are replacing traditional films and CCD sensors in the field of machine vision and scientific research for high-precision image acquisition.
However, CMOS image sensors still have many disadvantages and sometimes cannot meet the high precision requirements in the field of machine vision. For example, if the CMOS image sensor chip has a defect of large low bit noise, high accuracy of image acquisition cannot be well embodied.
Therefore, it is becoming more important how to examine the performance of CMOS image sensors used in the field of machine vision and the like under the requirement of high precision.
Disclosure of Invention
The present invention is directed to overcoming the above-mentioned drawbacks of the prior art and providing a method for detecting defects of a CMOS image sensor for machine vision.
In order to achieve the purpose, the technical scheme of the invention is as follows:
a defect detection method of a CMOS image sensor comprises the following steps:
the method comprises the following steps: collecting a gray card image by using an industrial camera containing a CMOS image sensor;
step two: preprocessing a gray card image to obtain a gray scale image;
step three: carrying out data shift processing on each pixel value in the gray-scale image to obtain a low-order image;
step four: averaging all pixel values in the low-order image to obtain an image mean value;
step five: respectively carrying out absolute value calculation on each pixel value in the low-order image and the image mean value to obtain a difference image;
step six: calculating the standard deviation of each pixel value in the difference image;
step seven: and when the obtained standard deviation is larger than a preset standard deviation threshold value, judging that the CMOS image sensor chip has the defect that the bottom noise of the low-order image exceeds the standard.
Further, in the first step, the gray card image is a black-and-white image obtained by a black-and-white system or a color image obtained by a color system.
Further, in the first step, the gray card image is a neutral gray image obtained by shooting a gray card with 18% reflectivity by using a normal exposure.
Further, in the first step, the gray card image is an image in RAW format, JPEG format, BMP format, PNG format, or TIFF format.
Further, in step two, the preprocessing includes:
judging whether the gray card image is a black-and-white image or a color image; wherein
When the gray card image is a black-and-white image, the gray card image is directly used as the gray image;
and when the gray card image is a color image, converting the gray card image into the gray image for use.
Further, in the third step, when the data shift processing is performed, and the grayscale map is an 8-bit image, the data of each pixel value in the grayscale map is shifted to the left by 5 bits, and only the data information of the lower three bits is retained, so as to obtain the lower image.
Further, in the third step, when the data shift processing is performed, and the grayscale map is a 10-bit image, the data of each pixel value in the grayscale map is shifted to the left by 6 bits, and only the data information of the lower four bits is retained, so as to obtain the lower image.
Further, the preset standard deviation threshold value is 1.4-1.6 aiming at 8bit or 10bit images.
Further, the preset standard deviation threshold is 1.5.
According to the technical scheme, the gray scale image formed by the collected gray card image is subjected to data shift processing to obtain the low-order image, the pixel values in the low-order image are averaged to obtain the image mean value, the absolute value of each pixel value in the low-order image and the image mean value are respectively calculated to obtain the difference image, and finally the standard deviation calculation is carried out on each pixel value in the difference image, so that whether the bottom noise of the low-order image exceeds the standard or not of the CMOS image sensor chip can be judged according to the obtained standard deviation, and the testing requirement on the high-precision image sensor can be well met.
Drawings
Fig. 1 is a flow chart of a defect detection method of a CMOS image sensor according to a preferred embodiment of the invention.
FIG. 2 is an 8-bit gray card image artwork obtained according to the method of FIG. 1.
Fig. 3 is a lower image obtained after processing the gray card image original of fig. 2 according to the method of fig. 1.
Detailed Description
The following describes embodiments of the present invention in further detail with reference to the accompanying drawings.
In the following detailed description of the embodiments of the present invention, in order to clearly illustrate the structure of the present invention and to facilitate explanation, the structure shown in the drawings is not drawn to a general scale and is partially enlarged, deformed and simplified, so that the present invention should not be construed as limited thereto.
In the following detailed description of the present invention, please refer to fig. 1, in which fig. 1 is a flowchart illustrating a defect detection method of a CMOS image sensor according to a preferred embodiment of the present invention. As shown in fig. 1, the defect detection method of the CMOS image sensor of the present invention can be applied to the field of machine vision and scientific research, and can meet the test requirements for high-precision CMOS image sensors. The defect detection method of the CMOS image sensor can comprise the following steps:
step S1: collecting a uniform neutral gray image I(i,j)。
Firstly, obtaining a gray card; the gray card is 18% reflective. Then, an industrial camera containing a high-precision CMOS image sensor is used for photographing the gray card by adopting a standard exposure mode and a normal exposure amount, so that a gray card image derived from the gray card is acquired, and the formed gray card image becomes a uniform neutral gray image I(i,j)As shown in fig. 2. Where (i, j) represents the pixel coordinates (or pixel values, the same applies below) of the image.
In the RGB color mode, when R: g: b is 1: 1: 1, namely the red, green and blue values are equal, namely the neutral gray is obtained.
The obtained gray card image can be a black-and-white image obtained by a black-and-white industrial camera, namely a black-and-white system; or it may be a color image obtained by a color industrial camera, i.e., by a color system.
The gray card image obtained as described above may be an image in RAW format, JPEG format, BMP format, PNG format, or TIFF format. Among them, the RAW format image is the most preferable.
Step S2: carrying out image preprocessing to obtain a gray level image I0(i,j)。
Then, for the obtained gray card image I(i,j)And (4) carrying out pretreatment. The specific pretreatment method may include:
firstly, judging whether a gray card image is a black-and-white image or a color image; that is, it is necessary to first determine whether the gray card image is a black-and-white image obtained by a black-and-white industrial camera (adopting a black-and-white system) or a color image obtained by a color industrial camera (adopting a color system).
Then, the following two methods can be adopted for correspondence:
(1) if the gray card image is a black-and-white image, the gray card image is taken as a gray scale image I0(i,j)And the subsequent steps are directly used.
(2) If the gray card image is a color image, i.e. the gray card image is an image that has been interpolated into colors, it needs to be converted into a gray image I0(i,j)And then can be reused. And, the obtained gray-scale image I0(i,j)The following formula is satisfied:
I0(i,j)(R × 30+ G × 59+ B × 11+50)/100 formula one
Wherein R, G, B in formula one represents red, green, and blue pixels in the image, respectively.
Step S3: performing data shift to obtain a low-order image Ilow(i,j)。
In obtaining a gray scale image I0(i,j)Then, the gray scale image I can be aligned0(i,j)Performs data shift processing on each pixel value in the image to obtain a lower image Ilow(i,j)。
For example, if the gray-scale image I is subjected to the data shift process0(i,j)When the image is 8bit, the data of each pixel value in the 8bit gray scale image can be shifted to the left by 5 bits, and only the data information of the lower three bits is reserved, thereby obtaining a lower bit image Ilow(i,j)。
If the gray-scale image is 10bit image, the data of each pixel value in the 10bit gray-scale image can be shifted to the left by 6 bits, and only the data information of the lower four bits is reservedThereby obtaining a low-order image Ilow(i,j)。
The data shift processing of the gray level image in the step can play a role in intercepting and amplifying the low-order image.
The data shift processing method of other bit images can be analogized accordingly.
Step S4: taking the mean value to obtain the image mean value Iavg。
In obtaining a low-order image Ilow(i,j)Then, the low-order image I can be processedlow(i,j)Is arithmetically averaged to obtain an image mean value Iavg。
Step S5: calculating absolute value to obtain difference image Idiff(i,j)。
At the time of obtaining the image mean value IavgThen, the lower image I is neededlow(i,j)Respectively with the image mean value IavgSubtracting, and calculating absolute value (ABS function) to obtain difference image Idiff(i,j). The difference image I obtaineddiff(i,j)The following formula is satisfied:
Idiff(i,j)＝ABS(Ilow(i,j)-Iavg) Formula II
Step S6: and calculating the standard deviation n of the difference image.
In obtaining a difference image Idiff(i,j)Then, the standard deviation (mean square error, STD function) calculation is performed on each pixel value in the difference image to obtain the standard deviation n. The standard deviation n satisfies the following formula:
n＝STD(Idiff(i,j)) Formula three
Step S7: the value of the standard deviation n is judged.
For an 8bit or 10bit image, the preset standard deviation threshold value can be 1.4-1.6. Preferably, the predetermined standard deviation threshold is 1.5.
When the obtained standard deviation n is larger than a preset standard deviation threshold value, the detected CMOS image sensor chip can be considered to have the defect that the bottom noise of a low-order image exceeds the standard, so that the high precision cannot be well embodied.
It should be noted that, in order to verify the scientificity and feasibility of the method of the present invention, the photographing quality of the gray card is artificially reduced, so that the obtained gray card image of fig. 2 is a less uniform image with obvious defects, but after the gray card image of fig. 2 is processed by the method of the present invention, the influence of the defective gray card image is completely eliminated as seen from the obtained lower image of fig. 3.
In summary, the present invention obtains the low-level image by performing data shift processing on the gray scale image formed by the collected gray card image, averages each pixel value in the low-level image to obtain an image mean value, performs absolute value calculation on each pixel value in the low-level image and the image mean value to obtain a difference image, and performs standard deviation calculation on each pixel value in the difference image, so that it can determine whether the CMOS image sensor chip has the defect that the bottom noise of the low-level image exceeds the standard according to the obtained standard deviation, thereby well meeting the test requirement for the high-precision image sensor.
The above description is only for the preferred embodiment of the present invention, and the embodiment is not intended to limit the scope of the present invention, so that all the equivalent structural changes made by using the contents of the description and the drawings of the present invention should be included in the scope of the present invention.
Claims (9)
1. A defect detection method of a CMOS image sensor is characterized by comprising the following steps:
the method comprises the following steps: collecting a gray card image by using an industrial camera containing a CMOS image sensor and adopting a standard exposure mode and normal exposure;
step two: preprocessing a gray card image to obtain a gray scale image;
step three: shifting the data of each pixel value in the gray-scale image to the left, and performing data shifting processing to obtain a low-order image;
step four: averaging all pixel values in the low-order image to obtain an image mean value;
step five: respectively carrying out absolute value calculation on each pixel value in the low-order image and the image mean value to obtain a difference image;
step six: calculating the standard deviation of each pixel value in the difference image;
step seven: and when the obtained standard deviation is larger than a preset standard deviation threshold value, judging that the CMOS image sensor chip has the defect that the bottom noise of the low-order image exceeds the standard.
2. The method for detecting defects of a CMOS image sensor as claimed in claim 1, wherein in the first step, the gray card image is a black-and-white image obtained in a black-and-white system or a color image obtained in a color system.
3. The method of claim 1, wherein in the first step, the gray card image is a neutral gray image obtained by taking a 18% reflectance gray card with a normal exposure.
4. The method of claim 1, wherein in the first step, the gray card image is an image in RAW format, JPEG format, BMP format, PNG format or TIFF format.
5. The method for detecting defects of a CMOS image sensor as claimed in claim 1, wherein in step two, the preprocessing comprises:
judging whether the gray card image is a black-and-white image or a color image; wherein
When the gray card image is a black-and-white image, the gray card image is directly used as the gray image;
and when the gray card image is a color image, converting the gray card image into the gray image for use.
6. The method for detecting defects of a CMOS image sensor as in claim 1, wherein in step three, when the data shift process is performed, and when the gray-scale image is an 8-bit image, the data of each pixel value in the gray-scale image is shifted to the left by 5 bits, and only the data information of the lower three bits is retained to obtain the lower image.
7. The method for detecting defects of a CMOS image sensor as in claim 1, wherein in step three, when the gray scale map is a 10bit image, the data of each pixel value in the gray scale map is shifted to the left by 6 bits, and only the data information of the lower four bits is retained to obtain the lower image.
8. The method for detecting the defects of the CMOS image sensor according to claim 1, wherein the preset standard deviation threshold is 1.4-1.6 for 8bit or 10bit images.
9. The method of claim 8, wherein the predetermined standard deviation threshold is 1.5.
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