CN107346431A - The dirty detection method of imaging sensor - Google Patents
The dirty detection method of imaging sensor Download PDFInfo
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- CN107346431A CN107346431A CN201610287134.5A CN201610287134A CN107346431A CN 107346431 A CN107346431 A CN 107346431A CN 201610287134 A CN201610287134 A CN 201610287134A CN 107346431 A CN107346431 A CN 107346431A
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- dirty
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/40—Extraction of image or video features
- G06V10/44—Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersections; Connectivity analysis, e.g. of connected components
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N17/00—Diagnosis, testing or measuring for television systems or their details
- H04N17/002—Diagnosis, testing or measuring for television systems or their details for television cameras
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30168—Image quality inspection
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- Computer Vision & Pattern Recognition (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Health & Medical Sciences (AREA)
- Biomedical Technology (AREA)
- General Health & Medical Sciences (AREA)
- Signal Processing (AREA)
- Image Processing (AREA)
Abstract
A kind of dirty detection method of imaging sensor, comprises the following steps：S1：Face lamp source plate shoots to obtain image G1；S2：Duplicating image G1 and binaryzation, obtain picture G2；S3：The central coordinate of circle (x0, y0) for calculating picture G2 sets radius R=1 pixels；S4：Circumferencial direction scan image G1；S5：Calculating pixel grey scale is found out doubtful dirty with mean difference on circumference；S6：Whether detection scanning area is completely out of image range；If it is not, into S7：Set radius R to increase by 1 pixel, be then back to S4；If so, into S8：Calculate the connected domain area of each doubtful dirty position；S9：Detect whether its connected domain area exceeds area threshold；If so, into S10：Export conclusion：It is dirty；If it is not, into S11：Export conclusion：Noise.Photograph can be recognized accurately with the presence or absence of dirty and dirty particular location in the dirty detection method of imaging sensor of the present invention, and can remove influence of the shade to image.
Description
Technical field
The present invention relates to a kind of dirty detection method of imaging sensor, especially one kind can
So that image sensing of the photograph with the presence or absence of dirty and dirty particular location is recognized accurately
The dirty detection method of device.
Background technology
Mobile phone camera module, camera, video camera need detected whether it is dirty, such as
Fruit has dirty, then needs to disassemble maintenance.The dirty mode of traditional detection is that face is uniform
Spread light source shooting image (photo), look for whether to exist from image it is dirty, this
Process judges mainly by human eye, but so efficiency is low, particularly extensive
Do not applied to during production.Although some manufacturers are automatically analyzed using computer software, generally
Image cutting is analyzed for the segment of homalographic, but due to uniformly diffusion light
Source take pictures exist intrinsic camera lens shade (Lens Shading, be the characteristic of camera lens,
Belong to normal phenomenon, bright surrounding is dark centered on it is showed) problem, cause operation time
It is long, and the degree of accuracy detected is very low, causes product quality unstable.
The content of the invention
In order to overcome drawbacks described above, the present invention provides a kind of dirty detection of imaging sensor
Photograph can be recognized accurately whether in method, the dirty detection method of described image sensor
Dirty and dirty particular location be present, and influence of the shade to image can be removed.
The present invention in order to solve its technical problem used by technical scheme be：One kind figure
As the dirty detection method of sensor, comprise the following steps：
S1：Face lamp source plate shoots to obtain image G1；
S2：Duplicating image G1 and binaryzation, obtain picture G2；
S3：The central coordinate of circle (x0, y0) for calculating picture G2 sets radius R=1 pixels；
S4：Circumferencial direction scan image G1；
S5：Calculating pixel grey scale is found out doubtful dirty with mean difference on circumference；
S6：Whether detection scanning area is completely out of image range；
If it is not, into S7：Set radius R to increase by 1 pixel, be then back to S4；
If so, into S8：Calculate the connected domain area of each doubtful dirty position；
S9：Detect whether its connected domain area exceeds area threshold；
If so, into S10：Export conclusion：It is dirty；
If it is not, into S11：Export conclusion：Noise.
The beneficial effects of the invention are as follows：The dirty detection method of imaging sensor of the present invention is led to
Cross calculating pixel grey scale and mean difference on circumference find out it is doubtful it is dirty after also to count
The connected domain area of each doubtful dirty position is calculated, only when the connected domain area of detection surpasses
Just be determined as when going out area threshold it is dirty, therefore, the dirty inspection of imaging sensor of the present invention
Photograph can be recognized accurately with the presence or absence of dirty and dirty particular location in survey method；Cause
For the dirty detection method of imaging sensor of the present invention be in circumferencial direction scan image, and
It is not to be analyzed image cutting for the segment of homalographic, therefore, it is possible to remove the moon
Influence of the shadow to image.
Brief description of the drawings
Fig. 1 is the theory diagram of the dirty detection method of imaging sensor of the present invention.
Fig. 2 is the image G1 of face lamp source plate shooting.
Fig. 3 is obtained black and white picture after the image G1 in copy pattern 2 and binaryzation
G2。
Fig. 4 is the signal of the picture G2 acquirement central coordinate of circle (x0, y0) in Fig. 3
Figure.
Fig. 5 is that image G1 in Fig. 2 with the coordinate (x0, y0) in Fig. 4 is circle
Scanning schematic diagram after the heart and setting different radii.
Fig. 6 is the schematic diagram that the Gray Level Jump position occurred on circumference is marked.
Fig. 7 is the connected domain area eventually detected beyond area threshold and is judged to
It is set to dirty schematic diagram.
The figures above is compareed, is supplemented as follows explanation：
S1--- face lamp source plates shoot to obtain image G1
S2--- duplicating images G1 and binaryzation, obtain picture G2
The central coordinate of circle (x0, y0) that S3--- calculates picture G2 sets radius R=1 pixels
S4--- circumferencial direction scan images G1
S5--- calculating pixel grey scales are found out doubtful dirty with mean difference on circumference
Whether S6--- detections scanning area is completely out of image range
S7--- sets radius R to increase by 1 pixel
S8--- calculates the connected domain area of each doubtful dirty position
S9--- detects whether its connected domain area exceeds area threshold and export conclusion
Embodiment
A kind of dirty detection method of imaging sensor, it is characterized in that：Comprise the following steps：
S1：Face lamp source plate shoots to obtain image G1；
S2：Duplicating image G1 and binaryzation, obtain picture G2；
S3：The central coordinate of circle (x0, y0) for calculating picture G2 sets radius R=1 pixels；
S4：Circumferencial direction scan image G1；
S5：Calculating pixel grey scale is found out doubtful dirty with mean difference on circumference；
S6：Whether detection scanning area is completely out of image range；
If it is not, into S7：Set radius R to increase by 1 pixel, be then back to S4；
If so, into S8：Calculate the connected domain area of each doubtful dirty position；
S9：Detect whether its connected domain area exceeds area threshold；
If so, into S10：Export conclusion：It is dirty；
If it is not, into S11：Export conclusion：Noise.
Dirty and noise difference is：Dirty is to have a piece of regional luminance ratio in image
Caused by surrounding is dark, the pixel of this panel region can be still imaged；Noise is on image
Noise pixel, such as there are several colored pixels inside a white picture, it is relatively tighter
The noise of weight is only bad point, and bad point can not be imaged.
Fig. 1 is the theory diagram of the dirty detection method of imaging sensor of the present invention.
Fig. 2-Fig. 7 is in embodiment, dirty according to imaging sensor of the present invention
Correspondence image obtained from each step operation of dirty detection method.
The dirty detection method of imaging sensor of the present invention is by calculating pixel grey scale and circle
On week mean difference find out it is doubtful it is dirty after also to calculate each doubtful dirty position
Connected domain area, just judge only when the connected domain area of detection exceeds area threshold
To be dirty.Therefore, the dirty detection method of imaging sensor of the present invention can accurately identify
Go out photograph with the presence or absence of dirty and dirty particular location；Because imaging sensor of the present invention
Dirty detection method be in circumferencial direction scan image, rather than image cutting for etc. face
Long-pending segment is analyzed, therefore, it is possible to remove influence of the shade to image.
Claims (1)
1. a kind of dirty detection method of imaging sensor, it is characterized in that：Including following step
Suddenly：
S1：Face lamp source plate shoots to obtain image G1；
S2：Duplicating image G1 and binaryzation, obtain picture G2；
S3：The central coordinate of circle (x0, y0) for calculating picture G2 sets radius R=1 pixels；
S4：Circumferencial direction scan image G1；
S5：Calculating pixel grey scale is found out doubtful dirty with mean difference on circumference；
S6：Whether detection scanning area is completely out of image range；
If it is not, into S7：Set radius R to increase by 1 pixel, be then back to S4；
If so, into S8：Calculate the connected domain area of each doubtful dirty position；
S9：Detect whether its connected domain area exceeds area threshold；
If so, into S10：Export conclusion：It is dirty；
If it is not, into S11：Export conclusion：Noise.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610287134.5A CN107346431A (en) | 2016-05-04 | 2016-05-04 | The dirty detection method of imaging sensor |
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| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610287134.5A CN107346431A (en) | 2016-05-04 | 2016-05-04 | The dirty detection method of imaging sensor |
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| Publication Number | Publication Date |
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| CN107346431A true CN107346431A (en) | 2017-11-14 |
Family
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| Application Number | Title | Priority Date | Filing Date |
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| CN201610287134.5A Pending CN107346431A (en) | 2016-05-04 | 2016-05-04 | The dirty detection method of imaging sensor |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108288264A (en) * | 2017-12-26 | 2018-07-17 | 横店集团东磁有限公司 | A kind of dirty test method of wide-angle camera module |
Citations (4)
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| CN102413354A (en) * | 2011-10-05 | 2012-04-11 | 深圳市联德合微电子有限公司 | Automatic optical detection method, device and system of mobile phone camera module |
| CN104143185A (en) * | 2014-06-25 | 2014-11-12 | 东软集团股份有限公司 | Blemish zone detecting method |
| CN104867159A (en) * | 2015-06-05 | 2015-08-26 | 北京大恒图像视觉有限公司 | Stain detection and classification method and device for sensor of digital camera |
| CN105259181A (en) * | 2015-10-26 | 2016-01-20 | 华为技术有限公司 | Display screen display defect detecting method, device and equipment |
-
2016
- 2016-05-04 CN CN201610287134.5A patent/CN107346431A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102413354A (en) * | 2011-10-05 | 2012-04-11 | 深圳市联德合微电子有限公司 | Automatic optical detection method, device and system of mobile phone camera module |
| CN104143185A (en) * | 2014-06-25 | 2014-11-12 | 东软集团股份有限公司 | Blemish zone detecting method |
| CN104867159A (en) * | 2015-06-05 | 2015-08-26 | 北京大恒图像视觉有限公司 | Stain detection and classification method and device for sensor of digital camera |
| CN105259181A (en) * | 2015-10-26 | 2016-01-20 | 华为技术有限公司 | Display screen display defect detecting method, device and equipment |
Non-Patent Citations (1)
| Title |
|---|
| 叶家和: "基于机器视觉的手机摄像头自动调焦", 《中国优秀硕士学位论文全文数据库-信息科技辑》 * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108288264A (en) * | 2017-12-26 | 2018-07-17 | 横店集团东磁有限公司 | A kind of dirty test method of wide-angle camera module |
| CN108288264B (en) * | 2017-12-26 | 2022-01-18 | 横店集团东磁有限公司 | Wide-angle camera module contamination testing method |
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