CN101729739A - Method for rectifying deviation of image - Google Patents
Method for rectifying deviation of image Download PDFInfo
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- CN101729739A CN101729739A CN200910193937A CN200910193937A CN101729739A CN 101729739 A CN101729739 A CN 101729739A CN 200910193937 A CN200910193937 A CN 200910193937A CN 200910193937 A CN200910193937 A CN 200910193937A CN 101729739 A CN101729739 A CN 101729739A
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Abstract
The invention provides a method for rectifying a derivation of an image, which comprises three steps of mathematical modelling, calculation of reverse mapping coordinates and image recovery. An optical path distortion imaging function of a lens of a video camera taking the image is defined, and corresponding parameters of the image are calculated; a mapping relationship between an actual imaging coordinate and an ideal imaging space coordinate is calculated by using the optical path distortion imaging function; a coordinate system of the mapping relationship is converted into an image coordinate system; reverse coordinate points of the distorted images are searched; the undistorted images are covered and output by means of image interpolations; the complicated function calculation is displayed by the simple mapping relationship of the image coordinates; the distorted images are analyzed automatically through conversion and mapping of various space coordinate systems by the method of combining the mathematical modelling and minimum error approaching analysis; all the required corrective parameters are extracted one by one and analyzed and stored on the basis of ensuring the arithmetic speed and the identification degree; and thus, the result integrates form, colour and quantity and the effect of rectifying the deviation of the image is improved.
Description
Technical field
The present invention relates to image processing techniques, particularly relate to a kind of processing method of rectifying a deviation for fault image.
Background technology
When take pictures with capture apparatus such as digital camera or mobile phones, during data such as business card, text, the image that was photographed tilts often, in addition, photo, business card, text etc. were that the object of rectangle distortion can take place and becomes arbitrary quadrilateral originally, and were especially obvious when amplifying.Its reason one be photographer not over against perpendicular on the subject, and exist certain horizontal range and deviation angle between the subject; The 2nd, the differentiation of every data parameters, the especially lens parameters of capture apparatus is far apart, causes the phenomenon of this distortion very common, people's data is read and handles cause difficulty.
Application number is 200410095109.4 patent, and patent name is image processing system and image processing method and electronic camera and image processing apparatus.This inventive images treatment system is made up of electrofax machine and image processing apparatus, the image that Electrofax photographs is presented on the monitor with regeneration mode, if the user needs the correction image distortion, need do it yourself to operate the quadrangle outline line that becomes benchmark when identification is revised, four apex coordinate information of the outline line selected are write the title portion of the image file of display image, carry out again afterwards and revise operation, its shortcoming is that the user needs manual operation, can't realize from dynamic(al) correction, process complexity, accuracy are not high.
Application number is 200610117277.8 patent, and patent name is the image processing method of picture distortion from dynamic(al) correction.Though this invention can realize the function from dynamic(al) correction, accuracy also improves relatively, but the identification degree also is nowhere near, when handling, distortion also needs the artificial judgement of confirming, be very much complicated on compute mode, will inevitably the speed of image processing be impacted, cause discrimination to reduce, not enough human oriented design, cost is higher.
In addition, the Photoshop software that everybody is familiar with also can be realized the distortion in images calibration function to a certain extent, but limitation is very big, at first be that it must be based upon on the basis of computer and could implement, need user's manual adjustments, proofread and correct, play up or the like, therefore in the operating process error can appear, accuracy is not high, more there is not function from dynamic(al) correction, next is that it can only carry out distortion correction at the image of simple image or single plane, then can't realize operation for the image of solids such as relative complex or 3D, be that it is more and more higher to the requirement of computer system and computer configuration once more, the computer of low side can't reach requirement or very slow on the speed of operation and reaction at all, is difficult to raise the efficiency.
Summary of the invention
The technological deficiency that purpose of the present invention exists at prior art just proposes a kind of method for rectifying deviation of image, can realize the distortion correction of multiple image and file, need not artificial participation, discern automatically and adjust, reaction fast, built-in function is simple and convenient, effectively raises the efficiency.
For achieving the above object, technical scheme of the present invention is achieved by following steps:
(1) carry out mathematical modeling: the optical path distortion that defines its capture apparatus camera lens at capture apparatus becomes transform, and the optical path distortion of its camera lens becomes the model definition of transform to be: (X`
Picture, Y`
Picture)=F[X
Picture, Y
Picture, A
Unknown], parameter A wherein
UnknownBe made as the matrix of m*n, by calculating the unknown parameter of determining its function, i.e. A
Unknown, and substitution real scene shooting distortion in images data, draw the known function of parameter;
(2) coordinate is oppositely hinted obliquely in calculating: utilize the relation of hinting obliquely at of optical path distortion imaging function calculation actual imaging coordinate and ideal image space coordinates, and convert this coordinate system of hinting obliquely at relation to image coordinate system;
(3) carrying out image recovers: utilize the relation of hinting obliquely at of previous step image coordinate, fault image is made the backward reference point search, utilize the image interpolation recovery and export non-fault image.
Carrying out mathematical modeling forms according to following steps:
A, take secondary a measurement and use the image target, promptly standard grid target is as the real scene shooting object, and calculates the ratio K between the camera lens object distance and image distance at this moment;
B, on target, set and be evenly distributed 100---200 key points, and give each key point allocation space coordinate (X
Thing, Y
Thing), utilize the ratio K between object distance and the image distance to calculate the pairing ideal image space coordinates of each key point (X on the target
Picture, Y
Picture), promptly desirable non-distortion imaging space coordinate;
C, target figure is carried out actual photographed, obtain having the target image of distortion, and on the target image of distortion, find out corresponding key point, and according to the pixel physical features of imageing sensor in the capture apparatus, calculate the image space coordinates of the key point of target image, the i.e. coordinate system of " image---image " conversion draws aberrant image space coordinate (X`
Picture, Y`
Picture);
D, (X`
Picture, Y`
Picture) and (X
Picture, Y
Picture) be updated to function model (X`
Picture, Y`
Picture)=F[X
Picture, Y
Picture, A
Unknown] in, draw the overdetermined equation group of function model and find the solution, draw parameter A
Unknown, the numerical value that further draws function model is that the optical path distortion of capture apparatus camera lens becomes transform in theory, in conjunction with the lens optical distortion parameter of capture apparatus and the contrast relationship of non-distortion light path imaging, adopts one by one approaching method, corrected parameter A
UnknownDraw A`, to reach the minimum correction error of operation, i.e. E≤B, E is the correction error, and B is for setting constant, and B establishes more for a short time, and then E is more little, and the calculating of corrected parameter A is then complicated more.
Calculate and oppositely hint obliquely at coordinate according to being the following steps formation:
A, utilize (the X` of function model
Picture, Y`
Picture)=F[X
Picture, Y
Picture, A
Unknown] calculate distortion (X` based on the image coordinate system
Picture, Y`
Picture)---non-distortion (X
Picture, Y
Picture) the relation of hinting obliquely between the coordinate, more this relation of hinting obliquely at is converted to based on imaging coordinate system (X
Figure, Y
Figure), the pixel physical features in conjunction with image inductor in the shooting module of capture apparatus carries out the calculating that image coordinate is oppositely hinted obliquely at;
B, generate image correcting error computing parameter, distortion based on imaging coordinate system---hinting obliquely between the non-distortion coordinate pixel concern and convert binary number to, exists with the form of binary number file;
The distortion image height H` and the non-distortion image height H of each sampled point in c, the taking-up lens optical distortion parameter, the image height H` that will distort converts image space coordinates (X` to
Picture, Y`
Picture), convert non-distortion image height H to image space coordinates (X
Picture, Y
Picture);
D, conversion resulting non-aberrant image space coordinate (X
Picture, Y
Picture) be updated to function model (X`
Picture, Y`
Picture)=F[X
Picture, Y
Picture, A
Unknown] in, calculate corresponding aberrant image space coordinate (X``
Picture, Y``
Picture), calculate (X`` again
Picture, Y``
Picture) and (X`
Picture, Y`
Picture) all side corrections error E, whether judge the correction error E≤set constant B, its result has two kinds, is respectively:
When the correction error E be≤during constant B, revised parameter A ` is updated to function model (X`
Picture, Y`
Picture)=F[X
Picture, Y
Picture, A
Unknown] in, draw final function F;
When the correction error E be not≤during constant B, then turn back in the step of mathematical modeling, target figure is divided into the four sides, this moment, sampled point also was divided into four parts, if before the five equilibrium mistake has been arranged, then further was subdivided into four parts on this basis again, it is 4X4 part, utilize the step of mathematical modeling to calculate again, the sampled point under each face is found the solution primary parameter A` separately again, the corresponding A` that obtains
1, A`
2, A`
3, A`
4, and then obtain four images function F separately, i.e. F
+, F
2, F
3, F
4', and calculate corresponding aberrant again as coordinate points and all square correction error, obtain final function F equally;
E, search the physical size of image inductor, the unit of its size is um, and physical size is set at the rectangle frame of X*Y size, the central point of supposing image inductor is new image space coordinates initial point, datum point is to distance D x, the Dy of image inductor frame, Dx=X/2 then, Dy=Y/2;
The effective dimensions of f, the non-aberrant picture of calculating, its size is made as 2Rx*2Ry, the original shape of fault image, be that non-fault image is bigger 1.5 times than the size of fault image, calculate the effective dimensions of non-fault image, its size is made as the Px*Py pixel, if the size of each pixel is the square of a*a, unit is um, then Px=2Rx/a, Py=2Ry/a, that calculates non-each pixel of fault image oppositely hints obliquely at coordinate, and the initial value of Rx*Ry is set, and the initial value of Rx is made as 1.5xDx, the initial value of Ry is made as 1.5xDy, and is updated to function (X`
Picture, Y`
Picture)=F[X
Picture, Y
Picture, A
Unknown] in find the solution, then 2Rx and 2Ry are respectively the effective dimensions of non-aberrant as coordinate;
G, each pixel transitions of non-fault image is become corresponding image coordinate, with image coordinate substitution function (X`
Picture, Y`
Picture)=F[X
Picture, Y
Picture, A
Unknown] in, to try to achieve the coordinate points of corresponding aberrant picture, and coordinate points is changed back corresponding image pixel coordinate points, this pixel coordinate point promptly is positioned on the characteristics position of fault image.
Carrying out image recovers to form according to following steps:
A, establishment one width of cloth room map file, its size is made as Px*Py, forms Zou's shape of non-fault image;
B, the binary file that generates before reading in the map file of room are searched coordinate points corresponding to fault image according to the coordinate points of each pixel in the map file of room from binary file;
C, read in fault image, and carry out image interpolation and image cutting, guarantee image chroma value, pixel value and the unnecessary image edge part of removal with the form of bitmap;
D, complete non-fault image and the output correction image of generation.
The present invention compared with prior art has following obvious improvement and outstanding characteristics:
1---can not depend on unduly the lens parameters of capture apparatus, need not to carry out white accurate position compensation and correction, also can not produce the uneven situation of light source, and the complex calculations function is showed with the succinct image coordinate relation of hinting obliquely at, in conjunction with mathematical modeling and function model, the conversion by coordinate system between image and the image, hint obliquely at, interpolation, analyze automatically, on the basis that guarantees arithmetic speed and identification degree, promote correction speed and output effect;
2---and correction product on the existing market is in carrying out the distortion correction process, need repeat a plurality of steps, reach 30% image as a picture distortion amount, with traditional correction product or technology whenever by once carrying out 10% correction at most, 30% amount of distortion is minimum just to need repetitive operation three times, more loaded down with trivial details, by means of the present invention, on the practical operation step, more omit, response speed is faster, and the user does not need manual setting fully from photographing generation again to showing this whole process, can settle at one go, human oriented design, convenient simple and easy, and more accurate, because the present invention does not rely on the subjective sensation of user to each line position of photographic images, guarantee that last correction result is undistorted in shape;
3---the present invention can be directly be installed in the computer with the form of software and operates, but it is more simple and convenient than Photoshop software, requirement to hardware and software does not have so strict, the present invention also can be integrated on the chip, chip is installed on the various capture apparatus then, capture apparatus will be discerned image and proofread and correct and rectify a deviation automatically when taking, reach demonstration or export the image that comes and be complete and can not produce distortion, more flexible in form and convenient, enlarged use category and application, market prospects are huge.
Description of drawings
The invention will be further described below in conjunction with drawings and Examples.
Fig. 1 is an overview flow chart of the present invention;
Fig. 2 is the flow chart of mathematical modeling;
Fig. 3 calculates the flow chart of oppositely hinting obliquely at coordinate;
Fig. 4 is the flow chart that image recovers.
Embodiment
Extremely shown in Figure 4 according to Fig. 1, method for rectifying deviation of image of the present invention mainly is divided into mathematical modeling, calculates and oppositely hint obliquely at coordinate and carry out image recovery three big steps, in use, reference object is carried out in the process of image taking, at first be to take secondary a measurement to use the image target, be that standard grid target is as the real scene shooting object, and calculate ratio K between this moment camera lens object distance and image distance, on target, set and be evenly distributed 100---200 key points, and give each key point allocation space coordinate (X
Thing, Y
Thing), utilize the ratio K between object distance and the image distance to calculate the pairing ideal image space coordinates of each key point (X on the target
Picture, Y
Picture), it is desirable non-distortion imaging space coordinate, target figure is carried out actual photographed, obtain having the target image of distortion, and on the target image of distortion, find out corresponding key point, and, calculate the image space coordinates of the key point of target image according to the pixel physical features of imageing sensor in the capture apparatus, the i.e. coordinate system of " image---image " conversion draws aberrant image space coordinate (X`
Picture, Y`
Picture), (X`
Picture, Y`
Picture) and (X
Picture, Y
Picture) be updated to function model (X`
Picture, Y`
Picture)=F[X
Picture, Y
Picture, A
Unknown] in, draw the overdetermined equation group of function model and find the solution, draw parameter A
Unknown, the numerical value that further draws function model is that the optical path distortion of capture apparatus camera lens becomes transform in theory, in conjunction with the lens optical distortion parameter of capture apparatus and the contrast relationship of non-distortion light path imaging, adopts one by one approaching method, corrected parameter A
UnknownDraw A`, to reach the minimum correction error of operation, i.e. E≤B, E is the correction error, and B is for setting constant, and B establishes more for a short time, and then E is more little, and the calculating of corrected parameter A is then complicated more.
Next is to calculate oppositely to hint obliquely at coordinate, utilizes (the X` of function model
Picture, Y`
Picture)=F[X
Picture, Y
Picture, A
Unknown] calculate distortion (X` based on the image coordinate system
Picture, Y`
Picture)---non-distortion (X
Picture, Y
Picture) the relation of hinting obliquely between the coordinate, more this relation of hinting obliquely at is converted to based on imaging coordinate system (X
Figure, Y
Figure), pixel physical features in conjunction with image inductor in the shooting module of capture apparatus, carry out the calculating that image coordinate is oppositely hinted obliquely at, generate image correcting error computing parameter, distortion based on imaging coordinate system---the relation of hinting obliquely between the non-distortion coordinate pixel converts binary number to, form with the binary number file exists, and takes out the distortion image height H` and the non-distortion image height H of each sampled point in the lens optical distortion parameter, and the image height H` that will distort converts image space coordinates (X` to
Picture, Y`
Picture), convert non-distortion image height H to image space coordinates (X
Picture, Y
Picture), the resulting non-aberrant of conversion image space coordinate (X
Picture, Y
Picture) be updated to function model (X`
Picture, Y`
Picture)=F[X
Picture, Y
Picture, A
Unknown] in, calculate corresponding aberrant image space coordinate (X``
Picture, Y``
Picture), calculate (X`` again
Picture, Y``
Picture) and (X`
Picture, Y`
Picture) all side corrections error E, whether judge the correction error E≤set constant B, its result has two kinds, is respectively:
When the correction error E be≤during constant B, revised parameter A ` is updated to function model (X`
Picture, Y`
Picture)=F[X
Picture, Y
Picture, A
Unknown] in, draw final function F.
When the correction error E be not≤during constant B, then turn back in the step of mathematical modeling, target figure is divided into the four sides, this moment, sampled point also was divided into four parts, if before the five equilibrium mistake has been arranged, then further was subdivided into four parts on this basis again, it is 4X4 part, utilize the step of mathematical modeling to calculate again, the sampled point under each face is found the solution primary parameter A` separately again, the corresponding A` that obtains
1, A`
2, A`
3, A`
4, and then obtain four images function F separately, i.e. F
+, F
2, F
3, F
4', and calculate corresponding aberrant again as coordinate points and all square correction error, obtain final function F equally.
Search the physical size of image inductor again, the unit of its size is um, physical size is set at the rectangle frame of X*Y size, the central point of supposing image inductor is new image space coordinates initial point, and datum point is to the distance D x of image inductor frame, Dy, then Dx=X/2, Dy=Y/2, calculate the effective dimensions of non-aberrant picture, its size is made as 2Rx*2Ry, the original shape of fault image, be that non-fault image is bigger 1.5 times than the size of fault image, calculate the effective dimensions of non-fault image, its size is made as the Px*Py pixel, and the size of establishing each pixel is the square of a*a, unit is um, Px=2Rx/a then, Py=2Ry/a, that calculates non-each pixel of fault image oppositely hints obliquely at coordinate, the initial value of Rx*Ry is set, the initial value of Rx is made as 1.5xDx, and the initial value of Ry is made as 1.5xDy, and is updated to function (X`
Picture, Y`
Picture)=F[X
Picture, Y
Picture, A
Unknown] in find the solution, then 2Rx and 2Ry are respectively the effective dimensions of non-aberrant as coordinate, and each pixel transitions of non-fault image is become corresponding image coordinate, with image coordinate substitution function (X`
Picture, Y`
Picture)=F[X
Picture, Y
Picture, A
Unknown] in, to try to achieve the coordinate points of corresponding aberrant picture, and coordinate points is changed back corresponding image pixel coordinate points, this pixel coordinate point promptly is positioned on the characteristics position of fault image.
Carrying out image once more recovers, create a width of cloth room map file, its size is made as Px*Py, form Zou's shape of non-fault image, the binary file that generates before in the map file of room, reading in, from binary file, search coordinate points according to the coordinate points of each pixel in the map file of room corresponding to fault image, form with bitmap is read in fault image, and carry out the cutting of image interpolation and image, preserve image chroma value, pixel value and the unnecessary image edge part of removal, generate complete non-fault image and output correction image.
The foregoing description is only enumerated for explanation the present invention, is not to be used to limit the present invention, and the structure of any effects equivalent based on the conversion of the technical program institute all belongs to protection scope of the present invention.
Claims (4)
1. a method for rectifying deviation of image is characterized in that, may further comprise the steps:
(1) carry out mathematical modeling: the parameter according to the capture apparatus camera lens becomes transform with the optical path distortion that defines described capture apparatus camera lens, and the optical path distortion of its camera lens becomes the model definition of transform to be: (X`
Picture, Y`
Picture)=F[X
Picture, Y
Picture, A
Unknown], by calculating the unknown parameter A that determines in the function F
UnknownValue, with the A after calculating
UnknownValue substitution real scene shooting distortion in images data in, to draw the function of having determined known parameters;
(2) calculate and oppositely to hint obliquely at coordinate: utilize optical path distortion imaging function calculation to go out the relation of hinting obliquely at of actual imaging coordinate and ideal image space coordinates, and convert this coordinate system of hinting obliquely at relation to image coordinate system;
(3) carrying out image recovers: utilize the relation of hinting obliquely at of step (2), fault image is made the backward reference point search, utilize the image interpolation recovery and export non-fault image.
2. a kind of method for rectifying deviation of image according to claim 1 is characterized in that: the described mathematical modeling that carries out of step (1) forms according to following steps:
A, take secondary a measurement and use the image target, promptly standard grid target is as the real scene shooting object, and calculates the ratio K between the camera lens object distance and image distance at this moment;
B, on target, set and be evenly distributed 100---200 key points, and give each key point allocation space coordinate (X
Thing, Y
Thing), utilize the ratio K between object distance and the image distance to calculate the pairing ideal image space coordinates of each key point (X on the target
Picture, Y
Picture), promptly desirable non-distortion imaging space coordinate;
C, target figure is carried out actual photographed, obtain having the target image of distortion, and on the target image of distortion, find out corresponding key point, and according to the pixel physical features of imageing sensor in the capture apparatus, calculate the image space coordinates of the key point of target image, the i.e. coordinate system of " image---image " conversion draws aberrant image space coordinate (X`
Picture, Y`
Picture);
D, (X`
Picture, Y`
Picture) and (X
Picture, Y
Picture) be updated to function model (X`
Picture, Y`
Picture)=F[X
Picture, Y
Picture, A
Unknown] in, draw the overdetermined equation group of function model and find the solution, draw parameter A
Unknown, the numerical value that further draws function model is that the optical path distortion of capture apparatus camera lens becomes transform in theory, in conjunction with the lens optical distortion parameter of capture apparatus and the contrast relationship of non-distortion light path imaging, adopts one by one approaching method, corrected parameter A
UnknownDraw A`, to reach the minimum correction error of operation, i.e. E≤B, E is the correction error, B is for setting constant.
3. a kind of method for rectifying deviation of image according to claim 1 is characterized in that: the described calculating of step (2) is oppositely hinted obliquely at coordinate and is formed according to following steps:
A, utilize (the X` of function model
Picture, Y`
Picture)=F[X
Picture, Y
Picture, A
Unknown] calculate distortion (X` based on the image coordinate system
Picture, Y`
Picture)---non-distortion (X
Picture, Y
Picture) the relation of hinting obliquely between the coordinate, more this relation of hinting obliquely at is converted to based on imaging coordinate system (X
Figure, Y
Figure), the pixel physical features in conjunction with image inductor in the shooting module of capture apparatus carries out the calculating that image coordinate is oppositely hinted obliquely at;
B, generate image correcting error computing parameter, distortion based on imaging coordinate system---hinting obliquely between the non-distortion coordinate pixel concern and convert binary number to, exists with the form of binary number file;
The distortion image height H` and the non-distortion image height H of each sampled point in c, the taking-up lens optical distortion parameter, the image height H` that will distort converts image space coordinates (X` to
Picture, Y`
Picture), convert non-distortion image height H to image space coordinates (X
Picture, Y
Picture);
D, conversion resulting non-aberrant image space coordinate (X
Picture, Y
Picture) be updated to function model (X`
Picture, Y`
Picture)=F[X
Picture, Y
Picture, A
Unknown] in, calculate corresponding aberrant image space coordinate (X``
Picture, Y``
Picture), calculate (X`` again
Picture, Y``
Picture) and (X`
Picture, Y`
Picture) all side corrections error E, whether judge the correction error E≤set constant B, revise accordingly and calculate according to above-mentioned judged result then, be updated to function model (X`
Picture, Y`
Picture)=F[X
Picture, Y
Picture, A
Unknown] in, draw final function F;
E, search the physical size of image inductor, the unit of its size is um, and physical size is set at the rectangle frame of X*Y size, the central point of supposing image inductor is new image space coordinates initial point, datum point is to distance D x, the Dy of image inductor frame, Dx=X/2 then, Dy=Y/2;
The effective dimensions of f, the non-aberrant picture of calculating, its size is made as 2Rx*2Ry, the original shape of fault image, be that non-fault image is bigger 1.5 times than the size of fault image, calculate the effective dimensions of non-fault image, its size is made as the Px*Py pixel, if the size of each pixel is the square of a*a, unit is um, then Px=2Rx/a, Py=2Ry/a, that calculates non-each pixel of fault image oppositely hints obliquely at coordinate, and the initial value of Rx*Ry is set, and the initial value of Rx is made as 1.5xDx, the initial value of Ry is made as 1.5xDy, and is updated to function (X`
Picture, Y`
Picture)=F[X
Picture, Y
Picture, A
Unknown] in find the solution, then 2Rx and 2Ry are respectively the effective dimensions of non-aberrant as coordinate;
G, each pixel transitions of non-fault image is become corresponding image coordinate, with image coordinate substitution function (X`
Picture, Y`
Picture)=F[X
Picture, Y
Picture, A
Unknown] in, to try to achieve the coordinate points of corresponding aberrant picture, and coordinate points is changed back corresponding image pixel coordinate points, this pixel coordinate point promptly is positioned on the characteristics position of fault image.
4. a kind of method for rectifying deviation of image according to claim 1 is characterized in that: the described image that carries out of step (3) recovers to form according to following steps:
A, establishment one width of cloth room map file, its size is made as Px*Py;
B, the binary file that generates before reading in the map file of room are searched coordinate points corresponding to fault image according to the coordinate points of each pixel in the map file of room from binary file;
C, read in fault image, and carry out image interpolation and image cutting with the form of bitmap;
D, complete non-fault image and the output correction image of generation.
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|---|---|---|---|
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Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102156969A (en) * | 2011-04-12 | 2011-08-17 | 潘林岭 | Processing method for correcting deviation of image |
| WO2013017046A1 (en) * | 2011-08-04 | 2013-02-07 | 中国移动通信集团公司 | Method and device for implementing program interface in application, computer program and storage medium |
| CN103822594A (en) * | 2014-02-28 | 2014-05-28 | 华南理工大学 | Workpiece scanning imaging method based on laser sensor and robot |
| CN106395528A (en) * | 2015-07-27 | 2017-02-15 | 株式会社日立制作所 | Parameter adjustment method, parameter adjustment device for range image sensor and elevator system |
| CN110766620A (en) * | 2019-09-27 | 2020-02-07 | 中国科学院苏州生物医学工程技术研究所 | Confocal endoscope image distortion correction method based on optical fiber probe |
-
2009
- 2009-11-16 CN CN200910193937A patent/CN101729739A/en active Pending
Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102156969A (en) * | 2011-04-12 | 2011-08-17 | 潘林岭 | Processing method for correcting deviation of image |
| CN102156969B (en) * | 2011-04-12 | 2013-09-25 | 潘林岭 | Processing method for correcting deviation of image |
| WO2013017046A1 (en) * | 2011-08-04 | 2013-02-07 | 中国移动通信集团公司 | Method and device for implementing program interface in application, computer program and storage medium |
| CN103822594A (en) * | 2014-02-28 | 2014-05-28 | 华南理工大学 | Workpiece scanning imaging method based on laser sensor and robot |
| CN106395528A (en) * | 2015-07-27 | 2017-02-15 | 株式会社日立制作所 | Parameter adjustment method, parameter adjustment device for range image sensor and elevator system |
| CN106395528B (en) * | 2015-07-27 | 2018-08-07 | 株式会社日立制作所 | Parameter regulation means, parameter adjustment controls and the elevator device of range image sensor |
| CN110766620A (en) * | 2019-09-27 | 2020-02-07 | 中国科学院苏州生物医学工程技术研究所 | Confocal endoscope image distortion correction method based on optical fiber probe |
| CN110766620B (en) * | 2019-09-27 | 2022-07-19 | 中国科学院苏州生物医学工程技术研究所 | Confocal endoscope image distortion correction method based on optical fiber probe |
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