CN100359448C - Method and system for instantly judging pick-up image pixel value abnormality - Google Patents
Method and system for instantly judging pick-up image pixel value abnormality Download PDFInfo
- Publication number
- CN100359448C CN100359448C CNB2004100620405A CN200410062040A CN100359448C CN 100359448 C CN100359448 C CN 100359448C CN B2004100620405 A CNB2004100620405 A CN B2004100620405A CN 200410062040 A CN200410062040 A CN 200410062040A CN 100359448 C CN100359448 C CN 100359448C
- Authority
- CN
- China
- Prior art keywords
- image
- pixel value
- value
- pick
- matching value
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Expired - Fee Related
Links
Images
Abstract
The present invention relates to a method and a system for instantly judging the abnormality of the pick-up image pixel value in an optical mouse, which judges the quality of an image picked up by the optical mouse in the video datum flow for determining the movement amount of the optical mouse. The process comprises a reference image pick-up step, a sampling image pick-up step, a matching value calculating step, a smoothing number calculating step, a local minimum number calculating step and an image quality judgment step. During the pretreatment, the quality of the image pixel picked up is judged. When the pixel value is abnormal and is not suitable to identify, the filtration and compensation are carried out in advance to improve the accuracy of moving vector calculated by a sampling image.
Description
Technical field
The present invention is about a kind of method and system of instantly judging pick-up image pixel value abnormality, refer to especially a kind of on optical mouse the method and system of instantly judging pick-up image pixel value abnormality.
Background technology
Known optical mouse has a video sensing device, and this video sensing device is made up of a plurality of image induction element, and the front and back image that utilizes this video sensing device to be sensed, and carries out the amount of movement detecting.And known applied optics mouse moving amount method for detecting is to search block (search block) with the partial image of first image as one, and carries out relevance (correlation) with this search block and second image at diverse location and calculate.Afterwards, find out absolute little value as displacement according to the relevance size of being calculated.
The example of the image when Fig. 1 is shown in the displacement method for detecting that carries out optical mouse.As the label among Fig. 1 130 is that label 110 among first image, Fig. 1 is that second image, 120 is for searching block, wherein, the size of first image 130 and second image 110 is the pixel (pixel) of 16*16, and the size of searching block 120 is the pixel of 8*8, that is to search block 120 be the image of the middle body 8*8 of first image 130, and the position of its central point is represented with X.After take out searching block 120, will search block 120 and move towards different directions, and respectively with second image 110 compute associations.Because the displacement of optical mouse is relevant with the speed of operator's mobile optical mouse, general first image 130 and second image 110 differ and are no more than 4 pixels, so when searching block 120 and second image 110 compute associations, to search block 120 central points and be positioned over the position that indicates circle (zero) in second image 110 respectively, calculate the relevance of this search block 120 and second image 110 again.The position that indicates circle (zero) in second image 110 has 81 places, so this method can produce 81 relevance numerical value C1～C81.Can find out the point of the most relevant property as displacement according to relevance numerical value C1～C81.
Yet, generally apply in the algorithm of optical mouse, because figure style on the mouse pad or dirt can produce unusual value to institute's pick-up image pixel, the exceptional value of these pixels is when carrying out the motion-vector estimation, can produce error to the motion-vector that estimates, and the error of motion-vector accumulation can influence the accuracy of motion-vector, so the method for detecting of known optical mouse amount of movement still remains improved space.
Summary of the invention
The object of the present invention is to provide a kind of method and system of instantly judging pick-up image pixel value abnormality, the accuracy when estimating can promote motion-vector.
According to a characteristic of the present invention, propose a kind of in optical mouse the method for instantly judging pick-up image pixel value abnormality, it judges that optical mouse captures the quality of an image in the video data stream, to determine the amount of movement of this optical mouse, this method comprises an acquisition and calculates matching value step, and calculate a number step and the image high-quality determining step that smoothing factor step, is calculated local minimum with reference to image step, an acquisition sampling image step.This captures with reference to the image step by image of acquisition in this video data stream, as the reference image; This acquisition sampling image step by one of acquisition in this video data stream at this with reference to the image image after, as the image of taking a sample; This calculating matching value step with reference to image and this sampling image, is calculated this sampling image with respect to this one group of matching value with reference to the possible motion-vector of image by this; This calculates the smoothing factor step, utilizes a filtering operation to calculate the smoothing factor of each matching value; This calculates the number step of local minimum, foundation one first rule is calculated and is the matching value number of local minimum in this group matching value, described first rule is meant: judge whether a smoothing factor revises matching value greater than one, if, the number of one local minimum is added one, and judge next aforementioned smoothing factor; Otherwise, judge next aforementioned smoothing factor, wherein, this correction matching value is multiplied by a correction factor with this matching value; And, this image high-quality determining step, whether the number of judging this local minimum is less than one first critical value, if then this sampling image is the high-quality image, by looking for minimum value in this group matching value, as the motion-vector of this sampling image.
According to another characteristic of the present invention, propose a kind of in optical mouse the system of instantly judging pick-up image pixel value abnormality, it judges that optical mouse captures the quality of an image in the video data stream, to determine the amount of movement of this optical mouse, this system comprises a light source, a pel array device, an analog/digital conversion device and a control device.This light source is in order to illuminate a sample plane; This pel array device is made up of a plurality of photo-sensitive cell, capturing this sample plane, and forms this video data stream; This analog/digital conversion device is coupled to this pel array device, to convert this video data stream to digital signal; This control device is coupled to this light source and this analog/digital conversion device, in order to the sequential of controlling the conversion of this analog/digital conversion device and the sequential of this light source igniting; Wherein, this control device is by image of acquisition in this video data stream, as the reference image, again by in this video data stream the acquisition one at this with reference to the image after the image, as the sampling image, then, calculate this sampling image with respect to this one group of matching value with reference to the possible motion-vector of image, utilize a filtering operation to calculate the smoothing factor of each matching value again, foundation one first rule is calculated and is the matching value number of local minimum in this group matching value, and described first rule is meant: whether judge a smoothing factor greater than a correction matching value, if, the number of one local minimum is added one, and judge next aforementioned smoothing factor; Otherwise, judge next aforementioned smoothing factor, wherein, this correction matching value is multiplied by a correction factor with this matching value; And whether the number of judging this local minimum is less than one first critical value, if then this sampling image is the high-quality image, by looking for minimum value in this group matching value, as the motion-vector of this sampling image.
Description of drawings
Fig. 1 is the synoptic diagram of known compute associations (correlation).
Fig. 2 is the calcspar of instantly judging pick-up image pixel value abnormality of the present invention system.
Fig. 3 is the process flow diagram of instantly judging pick-up image pixel value abnormality method of the present invention.
Fig. 4 A is the synoptic diagram of known optical mouse amount of movement of calculating when the mouse pad upper drawing circle.
The synoptic diagram of Fig. 4 B amount of movement of calculating that is optical mouse of the present invention when identical mouse pad upper drawing circle.
Fig. 5 A is the synoptic diagram of known optical mouse amount of movement of calculating when another mouse pad upper drawing circle.
Fig. 5 B is the synoptic diagram of optical mouse of the present invention amount of movement of calculating when another mouse pad upper drawing circle.
Symbol description among the figure:
130 second images 110 of first image
Analog/digital conversion is adorned 230 control device 240
Embodiment
Fig. 2 is the calcspar of the system of instantly judging pick-up image pixel value abnormality of the present invention, it is by in first image 130 in the video data stream shown in Figure 1 and second image 110, look in first image 130 one and search block 120 in second image 110 during corresponding motion-vector, judge whether this second image 110 is the high-quality image, if high-quality image, then export corresponding motion-vector, if non-prime image is then exported a default motion-vector.This system comprises a light source 210, a pel array device 220 (pixel array), an analog/digital conversion device 230, and a control device 240.
This light source 210 is in order to illuminate a sample plane, and it is preferably a light emitting diode.This pel array device 220 is made up of a plurality of photo-sensitive cell, capturing this sample plane, and forms this video data stream.This analog/digital conversion device 230 (Analogue to digital converter, ADC) is coupled to this pel array device 220, to convert this video data stream to digital signal.This control device 240 is coupled to this light source 210 and this analog/digital conversion device 230, the sequential of lighting in order to the sequential of controlling 230 conversions of this analog/digital conversion device and this light source 210.
And please refer to the process flow diagram of the method that Figure 3 shows that instantly judging pick-up image pixel value abnormality of the present invention, it is by in first image 130 in the video data stream shown in Figure 1 and second image 110, look in first image 130 one and search block 120 in second image 110 during corresponding motion-vector, judge whether this second image 110 is the high-quality image, if high-quality image, then export corresponding motion-vector, if non-prime image is then exported a default motion-vector.
As shown in Figure 3, at first in step S305, as the reference image, 130 conducts of first image of acquisition are with reference to image in present embodiment by image of acquisition in this video data stream.In step S310, by one of acquisition in this video data stream at this with reference to the image image after, as the sampling image, second image of acquisition 110 is as the images of taking a sample in present embodiment.
In step S315, calculate this sampling image with respect to this one group of matching value with reference to the possible motion-vector of image, in present embodiment, this group matching value C[i] [j] account form is also as shown in Figure 1, to search block 120 central points and be positioned over the position that indicates circle (zero) in second image 110 respectively, calculate the relevance of this search block 120 and second image 110 again, the position that indicates circle (zero) in second image 110 has 81 places, so, this method can produce 81 relevance numerical value, so this group matching value has 81 relevance numerical value C[i] [j], wherein 1≤i≤9,1≤j≤9 and i, j is an integer.
Step S320 calculates this group matching value C[i to step S335] smoothing factor of [j] and calculate this group matching value C[i according to one first rule] be the matching value number of local minimum in [j].In step S320, judge this group matching value C[i] whether [j] has all calculated corresponding smoothing factor, if corresponding smoothing factor has all been calculated in judgement, then execution in step S340 still has the matching value C[i that does not calculate if judge] [j], then execution in step S325.
In step S325, utilize a filtering operation to calculate each matching value C[i] the smoothing factor S[i of [j]] [j], this filtering operation is that a high-pass filtering is handled, it is with each matching value C[i] [j] matching value adjacent thereto and a high pass matrix carry out inner product and obtain a smoothing factor S[i] [j], in the middle of, this high pass matrix is a 3X3 matrix [010; 1n1; 010], this n value is one less than 0 constant, and in present embodiment, this n value is-4.
In step S330, judge this smoothing factor S[i] whether [j] revise matching value C ' [i] [j] greater than one, if, expression this matching value C[i then then] [j] be a local minimum, execution in step S335 adds 1 (variable n with the number of this local minimum
Local_min++), if judge this smoothing factor S[i] [j] be not more than and revise matching value C ' [i] [j], resumes step S320.Aforementioned process is referred to as first method, according to this first rule with this matching value C[i] [j] be multiplied by a correction factor G, to obtain the correction matching value C ' [i] [j] of a correspondence, wherein, this correction factor G is the constant greater than 0, and in present embodiment, this correction factor is 2.If this revises the smoothing factor S[i of matching value C ' [i] [j] less than correspondence] [j], then this matching value C[i] [j] be a local minimum.
In sum, first rule is meant: judge that whether a smoothing factor revise matching value greater than one, if the number of a local minimum is added one, and judge next aforementioned smoothing factor; Otherwise, judge next aforementioned smoothing factor, wherein, this correction matching value is multiplied by a correction factor with this matching value.
In step S340 is an image high-quality determining step, and it judges number (the variable n of this local minimum
Local_min) whether less than one first critical value (T1), if, represent that this sampling image (second image 110) is the high-quality image, then execution in step S345 returns 0 (n with the number of non-prime sampling image
Bad_image=0), by this group matching value C[i] look for minimum value in [j], as the motion-vector (step S350) of this sampling image.
In step S340, if judge number (the variable n of this local minimum
Local_min) non-less than this first critical value (T1), then this sampling image is non-prime image, then execution in step S365.In step S365, carry out one with reference to the image determining step, it judges number (the variable n of the sampling image of non-prime image
Bad_image) whether surpass one second critical value (T2), if not, represent that then this still can be with reference to image with reference to image (first image 130), execution in step S370 then is with the 1 (n that adds of the sampling image of non-prime image
Bad_image++), and export the motion-vector (step S375) of a default motion-vector as this sampling image.
In step S355, the motion-vector that motion-vector that execution in step S350 produced or rapid S375 are produced is as the motion-vector of this sampling image, and exports this motion-vector.
In step S360, judge whether this motion-vector surpasses this with reference to image boundary, if represent that then this can't be as the reference image with reference to image (first image 130), carry out one with reference to image step of updating (step S380), it is with reference to image with present sampling image setting.If be judged to be not, represent that then this still can be used as with reference to image resumes step S310 with reference to image (first image 130).
If step S365 judges number (the variable n of non-prime sampling image
Bad_image) surpass one second critical value (T2), represent that then this can't be as the reference image with reference to image (first image 130), execution one is with reference to image step of updating (step S380).
In the algorithm of known optical mouse, because figure style on the mouse pad or dirt can produce unusual value to institute's pick-up image pixel, and then influence the accuracy of motion-vector, shown in Fig. 4 A, when with a known optical mouse during at a mouse pad upper drawing circle, the amount of movement that causes optical mouse reality to be calculated owing to aforesaid influence is not to be a circle.Fig. 4 B for the optical mouse of using the technology of the present invention when same mouse pad upper drawing circle, the amount of movement that optical mouse is calculated.Fig. 5 A be known optical mouse when another mouse pad upper drawing circle, actual amount of movement of being calculated, Fig. 5 B for the optical mouse of using the technology of the present invention respectively when same mouse pad upper drawing circle, the amount of movement that optical mouse is calculated.Comparison diagram 4A and Fig. 4 B, Fig. 5 A and Fig. 5 B, the present invention judge promptly whether the sampling image is the sampling image of a high-quality when pre-treatment, so can increase the accuracy that the sampling image calculates motion-vector.
The foregoing description is only given an example for convenience of description, and the interest field that the present invention advocated should be as the criterion so that claim is described certainly, but not only limits to the foregoing description.
Claims (24)
1. the method for an instantly judging pick-up image pixel value abnormality, it judges that optical mouse captures the quality of an image in the video data stream,, is characterized in that this method comprises to determine the amount of movement of this optical mouse:
One acquisition is with reference to the image step, by image of acquisition in this video data stream, as the reference image;
One acquisition sampling image step, by one of acquisition in this video data stream at this with reference to the image image after, as the image of taking a sample;
One calculates the matching value step, with reference to image and this sampling image, calculates this sampling image with respect to this one group of matching value with reference to the possible motion-vector of image by this;
One calculates the smoothing factor step, utilizes a filtering operation to calculate the smoothing factor of each matching value;
One calculates the number step of local minimum, foundation one first rule is calculated and is the matching value number of local minimum in this group matching value, described first rule is meant: judge whether a smoothing factor revises matching value greater than one, if, the number of one local minimum is added one, and judge next aforementioned smoothing factor; Otherwise, judge next aforementioned smoothing factor, wherein, this correction matching value is multiplied by a correction factor with this matching value; And
Whether one image high-quality determining step, the number of judging this local minimum be less than one first critical value, if then this sampling image is the high-quality image, by looking for minimum value in this group matching value, as the motion-vector of this sampling image.
2. the method for instantly judging pick-up image pixel value abnormality as claimed in claim 1, wherein, in this image high-quality determining step, if judge that the number of this local minimum is non-less than one first critical value, then this sampling image is non-prime image, then with the motion-vector of a vector of presetting as this sampling image.
3. the method for instantly judging pick-up image pixel value abnormality as claimed in claim 2, it more comprises one with reference to the image step of updating, when it outnumbers one second critical value when non-prime sampling image, then upgrades this with reference to image.
4. the method for instantly judging pick-up image pixel value abnormality as claimed in claim 3, wherein, this non-prime sampling image number is continuous non-prime sampling image number.
5. the method for instantly judging pick-up image pixel value abnormality as claimed in claim 3, wherein, this upgrades this and substitutes this with reference to image with reference to image with a sampling image.
6. the method for instantly judging pick-up image pixel value abnormality as claimed in claim 1 wherein, is revised the smoothing factor of matching value less than correspondence as if this, and then this matching value is a local minimum.
7. the method for instantly judging pick-up image pixel value abnormality as claimed in claim 6, wherein, this correction factor is the constant greater than 0.
8. the method for instantly judging pick-up image pixel value abnormality as claimed in claim 7, wherein, this correction factor is 2.
9. the method for instantly judging pick-up image pixel value abnormality as claimed in claim 1 wherein, is calculated in the smoothing factor step in this, and this filtering operation is that a high-pass filtering is handled.
10. the method for instantly judging pick-up image pixel value abnormality as claimed in claim 9, wherein, this high-pass filtering is handled each a matching value matching value adjacent thereto and a high pass matrix is carried out inner product and obtain a smoothing factor, in the middle of, this high pass matrix is one 3 * 3 matrixes [0 10; 1 n 1; 010].
11. the method for instantly judging pick-up image pixel value abnormality as claimed in claim 10, wherein, this n value is one less than 0 constant.
12. the method for instantly judging pick-up image pixel value abnormality as claimed in claim 11, wherein, this n value is-4.
13. the system of an instantly judging pick-up image pixel value abnormality, it judges that optical mouse captures the quality of an image in the video data stream, and to determine the amount of movement of this optical mouse, this system comprises:
One light source, it is in order to illuminate a sample plane;
One pel array device, it is made up of a plurality of photo-sensitive cell, capturing this sample plane, and forms this video data stream;
One analog/digital conversion device is coupled to this pel array device, to convert this video data stream to digital signal; And
One control device is coupled to this light source and this analog/digital conversion device, in order to the sequential of controlling the conversion of this analog/digital conversion device and the sequential of this light source igniting;
Wherein, this control device is by image of acquisition in this video data stream, as the reference image, again by in this video data stream the acquisition one at this with reference to the image after the image, as the sampling image, then, calculate this sampling image with respect to this one group of matching value with reference to the possible motion-vector of image, utilize a filtering operation to calculate the smoothing factor of each matching value again, foundation one first rule is calculated and is the matching value number of local minimum in this group matching value, and described first rule is meant: whether judge a smoothing factor greater than a correction matching value, if, the number of one local minimum is added one, and judge next aforementioned smoothing factor; Otherwise, judge next aforementioned smoothing factor, wherein, this correction matching value is multiplied by a correction factor with this matching value; And whether the number of judging this local minimum is less than one first critical value, if then this sampling image is the high-quality image, by looking for minimum value in this group matching value, as the motion-vector of this sampling image.
14. the system of instantly judging pick-up image pixel value abnormality as claimed in claim 13, wherein, if this control device judges that the number of this local minimum is non-less than one first critical value, then this sampling image is non-prime image, then with the motion-vector of a vector of presetting as this sampling image.
15. the system of instantly judging pick-up image pixel value abnormality as claimed in claim 14 wherein, when judging that as if this control device non-prime sampling image outnumbers one second critical value, then upgrades this with reference to image.
16. the system of instantly judging pick-up image pixel value abnormality as claimed in claim 15, wherein, this non-prime sampling image number is continuous non-prime sampling image number.
17. the system of instantly judging pick-up image pixel value abnormality as claimed in claim 15, wherein, this upgrades this and substitutes this with reference to image with reference to image with a sampling image.
18. the system of instantly judging pick-up image pixel value abnormality as claimed in claim 13, wherein, if this revises the smoothing factor of matching value less than correspondence, then this matching value is a local minimum.
19. the system of instantly judging pick-up image pixel value abnormality as claimed in claim 18, wherein, this correction factor is the constant greater than 0.
20. the system of instantly judging pick-up image pixel value abnormality as claimed in claim 19, wherein, this correction factor is 2.
21. the system of instantly judging pick-up image pixel value abnormality as claimed in claim 13, wherein, this filtering operation is that a high-pass filtering is handled.
22. the system of instantly judging pick-up image pixel value abnormality as claimed in claim 21, wherein, this high-pass filtering is handled each a matching value matching value adjacent thereto and a high pass matrix is carried out inner product and obtain a smoothing factor, in the middle of, this high pass matrix is one 3 * 3 matrixes [0 10; 1 n1; 01 0].
23. the system of instantly judging pick-up image pixel value abnormality as claimed in claim 22, wherein, this n value is one less than 0 constant.
24. the system of instantly judging pick-up image pixel value abnormality as claimed in claim 23, wherein, this n value is-4.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CNB2004100620405A CN100359448C (en) | 2004-06-28 | 2004-06-28 | Method and system for instantly judging pick-up image pixel value abnormality |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CNB2004100620405A CN100359448C (en) | 2004-06-28 | 2004-06-28 | Method and system for instantly judging pick-up image pixel value abnormality |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN1716284A CN1716284A (en) | 2006-01-04 |
| CN100359448C true CN100359448C (en) | 2008-01-02 |
Family
ID=35822102
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CNB2004100620405A Expired - Fee Related CN100359448C (en) | 2004-06-28 | 2004-06-28 | Method and system for instantly judging pick-up image pixel value abnormality |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN100359448C (en) |
Families Citing this family (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN100524181C (en) * | 2006-04-27 | 2009-08-05 | 埃派克森微电子有限公司 | Optical motion sensing method |
| US20150212598A1 (en) * | 2014-01-28 | 2015-07-30 | Pixart Imaging Inc. | Dual mode optical navigation device and mode switching method thereof |
| US10365370B2 (en) * | 2016-10-31 | 2019-07-30 | Timothy Webster | Wear tolerant hydraulic / pneumatic piston position sensing using optical sensors |
| CN108021244A (en) * | 2016-11-03 | 2018-05-11 | 原相科技股份有限公司 | A kind of optics movement quality determination methods and optics movement quality judging system |
| US11734912B2 (en) * | 2021-05-05 | 2023-08-22 | Pixart Imaging Inc. | Computer readable recording medium which can be used to perform image quality improvement method and optical navigation method |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1410945A (en) * | 2001-09-25 | 2003-04-16 | 敦南科技股份有限公司 | Optical mouse chip having silicon retina structure |
| CN1417749A (en) * | 2001-11-06 | 2003-05-14 | 全视技术有限公司 | Method and device for determining relative motion of optical mouse |
| CN1487402A (en) * | 2002-10-02 | 2004-04-07 | ���ǵ�����ʽ���� | Single integrated circuit of optical mouse |
| US20040091165A1 (en) * | 2002-11-12 | 2004-05-13 | Keun-Woo Park | Method for processing image data of optical mouse |
-
2004
- 2004-06-28 CN CNB2004100620405A patent/CN100359448C/en not_active Expired - Fee Related
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1410945A (en) * | 2001-09-25 | 2003-04-16 | 敦南科技股份有限公司 | Optical mouse chip having silicon retina structure |
| CN1417749A (en) * | 2001-11-06 | 2003-05-14 | 全视技术有限公司 | Method and device for determining relative motion of optical mouse |
| CN1487402A (en) * | 2002-10-02 | 2004-04-07 | ���ǵ�����ʽ���� | Single integrated circuit of optical mouse |
| US20040091165A1 (en) * | 2002-11-12 | 2004-05-13 | Keun-Woo Park | Method for processing image data of optical mouse |
Also Published As
| Publication number | Publication date |
|---|---|
| CN1716284A (en) | 2006-01-04 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN111288967B (en) | Remote high-precision displacement detection method based on machine vision | |
| CN107804514B (en) | Toothbrush sorting method based on image recognition | |
| CN102253048A (en) | Machine vision detection method and system for detection of various products | |
| JP2011163766A (en) | Image processing method and image processing system | |
| NZ575499A (en) | System and method for adaptive non-uniformity compensation for a focal plane array | |
| CN103339466A (en) | Image processing device, and image processing program | |
| CN100359448C (en) | Method and system for instantly judging pick-up image pixel value abnormality | |
| CN101889452A (en) | Image generation device and image generation method | |
| JP6564409B2 (en) | System and method for processing event timing images | |
| CN102479321A (en) | Automatic identification system and method of difference image | |
| CN110689539A (en) | Workpiece surface defect detection method based on deep learning | |
| CN106612355B (en) | Production method and system for single correction production line of mobile phone camera module | |
| CN117232396B (en) | Visual detection system and method for product quality of high-speed production line | |
| JP2001086411A (en) | Solid-state image pickup device | |
| US8655024B2 (en) | Displacement detection device and displacement detection method thereof | |
| CN105000411B (en) | A kind of obbbin excess detection method based on machine vision technique | |
| US8717465B2 (en) | Blemish detection sytem and method | |
| CN103176349B (en) | Lens detection device and method | |
| CN111784575B (en) | Method for demosaicing monitoring camera based on calibration | |
| CN110689511B (en) | Optimization method for large-visual-field image splicing path | |
| KR100642499B1 (en) | Optical navigation device and method of operating of | |
| CN104794680A (en) | Multi-camera image mosaicking method and multi-camera image mosaicking device based on same satellite platform | |
| JP2010187409A (en) | Apparatus and method for correcting defects, and imaging apparatus | |
| US7362912B2 (en) | Method and system for immediately determining incorrect pixel values of a captured image | |
| US20090324019A1 (en) | Motion sensing method of sub-pixel level precision |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| C14 | Grant of patent or utility model | ||
| GR01 | Patent grant | ||
| CF01 | Termination of patent right due to non-payment of annual fee |
Granted publication date: 20080102 Termination date: 20150628 |
|
| EXPY | Termination of patent right or utility model |