CN100493207C - Distortion measurement and correction method for CCD shooting system and comprehensive test target - Google Patents
Distortion measurement and correction method for CCD shooting system and comprehensive test target Download PDFInfo
- Publication number
- CN100493207C CN100493207C CNB2007100643966A CN200710064396A CN100493207C CN 100493207 C CN100493207 C CN 100493207C CN B2007100643966 A CNB2007100643966 A CN B2007100643966A CN 200710064396 A CN200710064396 A CN 200710064396A CN 100493207 C CN100493207 C CN 100493207C
- Authority
- CN
- China
- Prior art keywords
- coordinate system
- image
- camera
- coordinate
- target
- 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 integrated testing target is composed of black/white interband and gray object points on the black/white interband. The method includes steps: establishing transformation relations between world coordinate system (CS) and camera CS, between pixel CS and image CS, between camera CS and image CS in sequence; collecting imaging polar coordinates (PC) of distortion image; plotting ideal imaging PC without distortion; determining coincidence relation between coordinate points (CP) of ideal image and CP of distortion image, and building polynomial model; based on polynomial coefficient to measure and correct distortion. The invention considers combined information of point target and row target for the integrated testing target. Using the integrated testing target replaces traditional three discrete target boards so as to solve issues of low position precision of target sample points, and difficult to make corresponding positions between target sampling points and image points.
Description
Technical field
The present invention relates to a kind of distortion measurement bearing calibration and comprehensive test target of CCD camera system, can be applicable to the distortion correction of TV guidance, space remote sensing, aerial mapping system, medical electronic endoscope, photoelectric guidance location, stereoscopic vision, robot navigation, monitoring and assembling automatically, robot vision etc., the distortion measurement correction that is specially adapted to have the CCD camera system of lacking the focal length characteristic in big visual field.Belong to optical imaging field.
Background technology
The CCD camera system and the camera lens of the short focal length in big visual field, because size is little, optical facilities are simpler, and its visual field is big, there is very big distortion in the image of shooting, has had a strong impact on image quality.
The mode that the distortion measurement of CCD camera system is proofreaied and correct research target plate demarcation commonly used realizes, by taking the fault image of space criteria sampling point target plate, grid target plate and grid-shaped target plate etc., its impact point is demarcated, set up distortion model, obtain distortion point and distortionless locus transformation relation, thereby realize the locus conversion of distortion.
World coordinate system is a rectangular coordinate system of testee and video camera being done as a whole consideration.Camera coordinate system is to be initial point with the video camera photocentre, the rectangular coordinate system of the optical axis coincidence of z axle and video camera.Pixel coordinate system is to be initial point with the image upper left corner, is the rectangular coordinate system of coordinate unit with the pixel.Image coordinate system be with optical axis be the rectangular coordinate system (Yu Qifeng etc., " based on the accurate measurement and the motion measurement of image ", Science Press, 2002) of initial point as the intersection point on plane
The normal target target surface that adopts is dot matrix, three target plates of row, column, as shown in Figure 1.Take the fault image of dot matrix, three target plates of row, column respectively, the ranks position that the capable image of utilization distortion and row image are determined each point, find out corresponding one by one between distortion point and the ideal point, this method algorithm is easy, has solved distortion point position problem one to one preferably.The weak point of this method is: 1, because target plate is too much, when taking fault image, all must change the target operation at every turn, operate too loaded down with trivial details; 2, target plate is as benchmark, and change target all needs the resetting center at every turn, repeatedly changes processing ease and causes the center off normal, influences positioning accuracy.
Summary of the invention
The objective of the invention is for overcoming the deficiency of above-mentioned prior art, a kind of distortion measurement bearing calibration of the CCD camera system based on comprehensive test target is proposed, solve the not high and corresponding difficult problem with its image point position of target sampled point of positional precision of target sampled point, the distortion measurement that is particularly useful for big visual field short focal length CCD camera system is proofreaied and correct.
Technical scheme of the present invention: at first make comprehensive test target, use tested CCD to take comprehensive test target to gather fault image, and extract its polar coordinates, demarcate desirable distortionless imaging polar coordinates then, by setting up between world coordinate system and the camera coordinate system, between pixel coordinate system and the image coordinate system, and the relation of the coordinate transform between camera coordinate system and the image coordinate system, set up the multinomial model between ideal image coordinate points and the fault image coordinate points, adopt least square method to calculate the multinomial coefficient of this model, measure the also distortion of correcting image thus.The comprehensive test target that this method is used be specially by between black and white between band and black and white with on the grey impact point constitute, wherein band is to be with between level between black and white, and vertical width of black-tape and leukorrhea equates, be uniform-distribution with delegation's grey impact point in every black-tape and the leukorrhea, these grey impact points align in vertical direction.
The distortion measurement bearing calibration of CCD camera system comprises following step:
1. set up the transformation relation between world coordinate system and the camera coordinate system: world coordinate system is rotated an angle around the x axle earlier, and then around angle of y axle rotation, at last around an angle of z axle rotation and obtain camera coordinate system, the translation matrix T that the coordinate of initial point in camera coordinate system of available above-mentioned spin matrix R that determines around the anglec of rotation of x axle, y axle and z axle and world coordinate system determined represents the transformation relation between world coordinate system and the camera coordinate system.
2. set up the transformation relation between pixel coordinate system and the image coordinate system: what the pixel coordinate of picture point was represented is line number and the columns that pixel is arranged in the digital picture matrix, the relation between available linear transformation relation expression pixel coordinate system and the image coordinate system.
3. set up the transformation relation between camera coordinate system and the image coordinate system: according to the imaging relations of object-image conjugate, an available nonlinear transformation is represented the transformation relation between camera coordinate system and the image coordinate system.
4. gather the imaging polar coordinates of fault image: obtain each impact point by the fault image of taking, and extract the center pixel coordinate of each impact point.Pixel coordinate system that sets up by step 2 and the transformation relation between the image coordinate system can become the center pixel Coordinate Conversion coordinate in the image coordinate system.At last the Coordinate Conversion in the image coordinate system being become with the image optical centre is the polar coordinates of limit, determines the imaging polar coordinates of fault image.
5. demarcate desirable distortionless imaging polar coordinates: with the comprehensive test target is benchmark, establish the world coordinate system position, while is the fixed cameras position also, at this moment can establish the external parameter spin matrix and the translation matrix of video camera, world coordinate system of setting up according to step 1 and the transformation relation between the camera coordinate system are coordinate in the camera coordinate system with the Coordinate Conversion of world coordinate system.Camera coordinate system of setting up according to step 3 and the transformation relation between the image coordinate system are coordinate in the image coordinate system with the Coordinate Conversion in the camera coordinate system.At last the Coordinate Conversion in the image coordinate system being become with the image optical centre is the polar coordinates of limit, determines desirable distortionless imaging polar coordinates.
6. determine the corresponding relation of ideal image coordinate points and fault image coordinate points respectively, set up multinomial model: the distortionless imaging polar coordinates of demarcating according to the imaging polar coordinates and the step 5 of the fault image that step 4 calculated, foundation comprises the multinomial model of n equation, by least square fitting evaluator coefficient, i.e. distortion factor.
7. measure also correcting distorted according to multinomial coefficient:,, obtain the locus of check point according to the distortion factor that step 6 is asked by scanning the locus that current fault image obtains pixel.The gray scale of the ignore in the correction chart can realize the gray scale reconstruction by the gray scale interpolation.
Another object of the present invention is to provide a kind of comprehensive test target of the CCD of being used for camera system distortion measurement correction, this comprehensive test target can be used in the distortion measurement bearing calibration or other distorted image correction method of above-mentioned CCD camera system.As shown in Figure 2, described comprehensive test target is made of the grey impact point on band and the black and white band between black and white.
Compare with existing method, comprehensive test target of the present invention has been taken some target and row target information into consideration.Wherein the grey impact point is the main demarcation information of some mark correspondence, and band is mainly used in the line number of differentiating grey impact point place in the fault image between black and white.Substitute three traditional discrete target plates with a comprehensive test target that comprises the capable information of grey impact point, when taking fault image at every turn, all needn't change target and resetting center, solve the not high and corresponding difficult problem of target sampled point of positional precision of target sampled point with its image point position.
Method of testing of the present invention adopts high accuracy distortion model and Digital Image Processing new technology and new algorithm, realizes high precision measurement and calibration to the distortion of big visual field CCD imaging system.
Description of drawings
The dot matrix that Fig. 1 adopts for prior art, the schematic diagram of row, column three target plates.
Fig. 2 is the schematic diagram of comprehensive test target of the present invention.
Embodiment
In order to understand technical scheme of the present invention better,, be described in further detail below in conjunction with drawings and Examples.
Adopt the inventive method, specifically carry out as follows:
1. set up the transformation relation between world coordinate system and the camera coordinate system: with world coordinate system (O, x
w, y
w, z
w) earlier around angle ω of x axle rotation, and then around angle of y axle rotation
, obtain camera coordinate system (O around a z axle angle φ of rotation at last
c, x
c, y
c, z
c), available above-mentioned anglec of rotation ω around x axle, y axle and z axle,
And the translation matrix T that determines of the coordinate of initial point in camera coordinate system of spin matrix R determining of φ and world coordinate system represents the transformation relation between world coordinate system and the camera coordinate system:
2. set up the transformation relation between pixel coordinate system and the image coordinate system: the pixel coordinate (x of picture point
f, y
f) what represent is line number and the columns that pixel is arranged in the digital picture matrix, the expression of the available linear transformation relation of the relation between pixel coordinate system and the image coordinate system:
x
f=s
xXu
+x
f0 (3)
y
f=s
yY
u+y
f0
S wherein
x, s
yBe the pixel count on the plane of delineation unit distance (pixels/mm), (x
F0, y
F0) be the pixel coordinate of camera optical axis and plane of delineation intersection point, X
uAnd Y
uBe respectively the coordinate of picture point in image coordinate system
3. set up the transformation relation between camera coordinate system and the image coordinate system: the ∏ of image coordinate system (x, y) plane overlaps with the perfect optics image planes, initial point is positioned at the photocentre place, the coordinate of photocentre in camera coordinate system be (0,0, f
e), f
eRepresent effective image distance.A bit (x of object space in the camera coordinate system
c, y
c, z
c) coordinate behind desirable lens imaging in image coordinate system be made as (z), according to the imaging relations of object-image conjugate, the transformation relation between camera coordinate system and the image coordinate system can be represented with a nonlinear transformation for x, y:
4. gather the imaging polar coordinates of fault image: at first obtain each impact point for the fault image of taking, and extract the center pixel coordinate of each impact point through the median filter smoothness of image preliminary treatment of image.Pixel coordinate system that sets up by step 2 and the transformation relation between the image coordinate system can become the center pixel Coordinate Conversion coordinate in the image coordinate system.At last the Coordinate Conversion in the image coordinate system being become with the image optical centre is the polar coordinates of limit, is the imaging polar coordinates (ρ of fault image
d, θ
d).
5. demarcate desirable distortionless imaging polar coordinates: with the comprehensive test target is benchmark, establish the world coordinate system position, camera position is fixed, at this moment can establish the external parameter spin matrix R and the translation matrix T of video camera, world coordinate system of setting up according to step 1 and the transformation relation between the camera coordinate system are coordinate in the camera coordinate system with the Coordinate Conversion of world coordinate system.Camera coordinate system of setting up according to step 3 and the transformation relation between the image coordinate system are coordinate in the image coordinate system with the Coordinate Conversion in the camera coordinate system.At last the Coordinate Conversion in the image coordinate system being become with the image optical centre is the polar coordinates of limit, determines desirable distortionless imaging polar coordinates (ρ
u, θ
u).
6. determine the corresponding relation of ideal image coordinate points and fault image coordinate points respectively, set up multinomial model:, set up the multinomial model that comprises n equation according to the distortionless imaging polar coordinates that the imaging polar coordinates and the step 5 of the fault image that step 4 calculated are demarcated:
(5)
By least square fitting evaluator coefficient a
1, a
2, a
3, a
4, a
5... a
mb
1, b
2, b
3, b
4, b
5... b
m, m is the multinomial model exponent number, its size is relevant with the computational accuracy of multinomial coefficient.
7. measure also correcting distorted according to multinomial coefficient: by scanning the locus (ρ that current fault image obtains pixel
d, θ
d), the distortion factor a that asks according to step 6
1, a
2, a
3, a
4, a
5... a
mb
1, b
2, b
3, b
4, b
5... b
m, obtain the locus (ρ of check point
c, θ
c) (the non-integer relation rounds):
(6)
The gray scale of the ignore in the correction chart can realize the gray scale reconstruction by the gray scale bilinear interpolation method.
Below in conjunction with the accompanying drawings the specific embodiment of the present invention is described; but these explanations can not be understood that to have limited scope of the present invention; protection scope of the present invention is limited by the claims of enclosing, and any change of carrying out on claim of the present invention basis all is protection scope of the present invention.
Claims (3)
1. the distortion measurement bearing calibration of a CCD camera system is characterized in that:
At first make comprehensive test target, comprehensive test target by between black and white the band and black and white between with on the grey impact point constitute, wherein band is to be with between level between black and white, and vertical width of black-tape and leukorrhea equates, be uniform-distribution with delegation's grey impact point in every black-tape and the leukorrhea, these grey impact points align in vertical direction;
Carry out following steps on this basis:
1) sets up transformation relation between world coordinate system and the camera coordinate system: world coordinate system is rotated a certain angle around x, y, z axle respectively, obtain camera coordinate system, the translation matrix determined of the coordinate of initial point in camera coordinate system of spin matrix of determining with above-mentioned each anglec of rotation around x, y and z axle and world coordinate system is represented the transformation relation between world coordinate system and the camera coordinate system then;
2) linear transformation of setting up between pixel coordinate system and the image coordinate system concerns that wherein, what the pixel coordinate of picture point was represented is line number and the columns that pixel is arranged in the digital picture matrix;
3), set up transformation relation between camera coordinate system and the image coordinate system by nonlinear transformation according to the imaging relations of object-image conjugate;
4) the imaging polar coordinates of collection fault image: obtain each impact point by the fault image of taking, and extract the center pixel coordinate of each impact point, by step 2) transformation relation between the pixel coordinate set up system and the image coordinate system, the center pixel Coordinate Conversion is become coordinate in the image coordinate system, at last the Coordinate Conversion in the image coordinate system being become with the image optical centre is the polar coordinates of limit, is the imaging polar coordinates of fault image;
5) demarcate desirable distortionless imaging polar coordinates: with the comprehensive test target is benchmark, establish the world coordinate system position, world coordinate system of setting up according to step 1) and the transformation relation between the camera coordinate system, with the Coordinate Conversion of world coordinate system is coordinate in the camera coordinate system, camera coordinate system of setting up according to step 3) and the transformation relation between the image coordinate system, with the Coordinate Conversion in the camera coordinate system is coordinate in the image coordinate system, at last the Coordinate Conversion in the image coordinate system being become with the image optical centre is the polar coordinates of limit, determines desirable distortionless imaging polar coordinates;
6) the undistorted imaging polar coordinates of demarcating according to the imaging polar coordinates and the step 5) of the fault image that step 4) calculated, foundation comprises the multinomial model of several equations, and the multinomial coefficient that calculates in the described multinomial model by least square fitting is a distortion factor;
7),, obtain the locus of check point according to the distortion factor that step 6) is asked by scanning the locus that current fault image obtains pixel.
2. as claim 1 described method, it is characterized in that, the concrete grammar that extracts the center pixel coordinate in the described step 4) is: by the fault image of taking is at first obtained each impact point through the median filter smoothness of image preliminary treatment of image, extract the center pixel coordinate of each impact point then.
3. the method for claim 1 is characterized in that, described step 7) also comprises step: realize the gray scale reconstruction by the gray scale interpolation, with the gray scale of ignore among the correcting distorted figure.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CNB2007100643966A CN100493207C (en) | 2007-03-14 | 2007-03-14 | Distortion measurement and correction method for CCD shooting system and comprehensive test target |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CNB2007100643966A CN100493207C (en) | 2007-03-14 | 2007-03-14 | Distortion measurement and correction method for CCD shooting system and comprehensive test target |
Publications (2)
Publication Number | Publication Date |
---|---|
CN101026778A CN101026778A (en) | 2007-08-29 |
CN100493207C true CN100493207C (en) | 2009-05-27 |
Family
ID=38744603
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CNB2007100643966A Expired - Fee Related CN100493207C (en) | 2007-03-14 | 2007-03-14 | Distortion measurement and correction method for CCD shooting system and comprehensive test target |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN100493207C (en) |
Cited By (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN101582161B (en) * | 2009-06-15 | 2012-11-21 | 北京航空航天大学 | C-type arm image correction method based on perspective imaging model calibration |
CN102853903A (en) * | 2011-06-28 | 2013-01-02 | 中国科学院西安光学精密机械研究所 | Method for demarcating linearity indexes of scientific grade Charge-coupled Device (CCD) |
CN101476844B (en) * | 2008-12-09 | 2013-06-05 | 南瑶 | Calibration method and standard target plate for carrier optoelectronic series on-site dynamic self-calibration |
Families Citing this family (18)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JP2011188083A (en) * | 2010-03-05 | 2011-09-22 | Sony Corp | Information processing apparatus, information processing method, program, and imaging apparatus including optical microscope |
CN104240216A (en) * | 2013-06-07 | 2014-12-24 | 光宝电子(广州)有限公司 | Image correcting method, module and electronic device thereof |
CN103366555B (en) * | 2013-07-01 | 2015-06-17 | 中国人民解放军第三军医大学第三附属医院 | Aerial image-based traffic accident scene image rapid generation method and system |
CN103793112B (en) * | 2014-03-10 | 2018-06-19 | 天津津航技术物理研究所 | The calibration method and system of a kind of touch screen |
CN105631875A (en) * | 2015-12-25 | 2016-06-01 | 广州视源电子科技股份有限公司 | Method and system for determining mapping relations between camera coordinates and arm gripper coordinates |
CN105955260B (en) * | 2016-05-03 | 2019-05-17 | 大族激光科技产业集团股份有限公司 | Position of mobile robot cognitive method and device |
CN106485753B (en) * | 2016-09-09 | 2019-09-10 | 奇瑞汽车股份有限公司 | The method and apparatus of camera calibration for pilotless automobile |
CN106292673B (en) * | 2016-09-29 | 2019-02-12 | 深圳大学 | A kind of method for optimizing route and system |
CN106485758B (en) * | 2016-10-31 | 2023-08-22 | 成都通甲优博科技有限责任公司 | Unmanned aerial vehicle camera calibration device, calibration method and assembly line calibration implementation method |
CN109410426A (en) * | 2017-01-23 | 2019-03-01 | 合肥智慧龙图腾知识产权股份有限公司 | The bus of Internet of Things interactive terminal is installed |
CN107977977B (en) * | 2017-10-20 | 2020-08-11 | 深圳华侨城卡乐技术有限公司 | Indoor positioning method and device for VR game and storage medium |
CN110139093B (en) * | 2019-04-11 | 2021-06-11 | 歌尔光学科技有限公司 | Method and device for acquiring camera view field distortion and electronic equipment |
CN110864878A (en) * | 2019-10-14 | 2020-03-06 | 中国航空工业集团公司洛阳电光设备研究所 | Method for detecting display distortion of high-efficiency large-view-field flat display system |
CN111383194B (en) * | 2020-03-10 | 2023-04-21 | 江苏科技大学 | Polar coordinate-based camera distortion image correction method |
CN111899366A (en) * | 2020-07-27 | 2020-11-06 | 上海福赛特智能科技有限公司 | Method for accurately positioning hairpin point |
CN111982072B (en) * | 2020-07-29 | 2022-07-05 | 西北工业大学 | Target ranging method based on monocular vision |
CN112588621B (en) * | 2020-11-30 | 2022-02-08 | 山东农业大学 | Agricultural product sorting method and system based on visual servo |
CN117115275B (en) * | 2023-10-25 | 2024-03-12 | 深圳明锐理想科技股份有限公司 | Distortion parameter determination method and device and computer equipment |
Citations (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN1508512A (en) * | 2002-12-17 | 2004-06-30 | 北京航空航天大学 | Overall calibrating method for multi-vision sensor detecting system |
CN1508527A (en) * | 2002-12-17 | 2004-06-30 | 北京航空航天大学 | Method for calibarting lens anamorphic parameter |
CN1566906A (en) * | 2003-06-11 | 2005-01-19 | 北京航空航天大学 | Construction optical visual sense transducer calibration method based on plane targets |
-
2007
- 2007-03-14 CN CNB2007100643966A patent/CN100493207C/en not_active Expired - Fee Related
Patent Citations (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN1508512A (en) * | 2002-12-17 | 2004-06-30 | 北京航空航天大学 | Overall calibrating method for multi-vision sensor detecting system |
CN1508527A (en) * | 2002-12-17 | 2004-06-30 | 北京航空航天大学 | Method for calibarting lens anamorphic parameter |
CN1566906A (en) * | 2003-06-11 | 2005-01-19 | 北京航空航天大学 | Construction optical visual sense transducer calibration method based on plane targets |
Non-Patent Citations (4)
Title |
---|
大视场短焦距CCD成像系统畸变校正研究. 张华达.红外,第2004年第1期. 2004 |
大视场短焦距CCD成像系统畸变校正研究. 张华达.红外,第2004年第1期. 2004 * |
大视场短焦距镜头CCD摄像系统的畸变校正. 行麦玲,刘贱平,林家明,沙定国,苏大图.光学技术,第2003年03期. 2003 |
大视场短焦距镜头CCD摄像系统的畸变校正. 行麦玲,刘贱平,林家明,沙定国,苏大图.光学技术,第2003年03期. 2003 * |
Cited By (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN101476844B (en) * | 2008-12-09 | 2013-06-05 | 南瑶 | Calibration method and standard target plate for carrier optoelectronic series on-site dynamic self-calibration |
CN101582161B (en) * | 2009-06-15 | 2012-11-21 | 北京航空航天大学 | C-type arm image correction method based on perspective imaging model calibration |
CN102853903A (en) * | 2011-06-28 | 2013-01-02 | 中国科学院西安光学精密机械研究所 | Method for demarcating linearity indexes of scientific grade Charge-coupled Device (CCD) |
CN102853903B (en) * | 2011-06-28 | 2014-07-02 | 中国科学院西安光学精密机械研究所 | Method for demarcating linearity indexes of scientific grade Charge-coupled Device (CCD) |
Also Published As
Publication number | Publication date |
---|---|
CN101026778A (en) | 2007-08-29 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN100493207C (en) | Distortion measurement and correction method for CCD shooting system and comprehensive test target | |
US7715644B2 (en) | Image calibration method, image calibration processing device, and image calibration processing terminal | |
CN105513072A (en) | PTZ correction method | |
CN112254663B (en) | Plane deformation monitoring and measuring method and system based on image recognition | |
CN105118055A (en) | Camera positioning correction calibration method and system | |
CN201690518U (en) | Embedded fisheye image real-time distortion correction device based on FPGA | |
CN106780391B (en) | Distortion correction algorithm for optical system of full-view three-dimensional measuring instrument | |
CN101261737A (en) | 2-dimensional marking device and marking method for digital aviation measuring camera | |
CN111307046B (en) | Tree height measuring method based on hemispherical image | |
CN106709912A (en) | Automatic testing system and testing method for preset position precision | |
CN111383194A (en) | Camera distortion image correction method based on polar coordinates | |
CN111986267B (en) | Coordinate system calibration method of multi-camera vision system | |
CN106447733A (en) | Cervical vertebra motion degree and motion axial line position determining method, system and device | |
CN113947638B (en) | Method for correcting orthographic image of fish-eye camera | |
CN106023193A (en) | Array camera observation method for detecting structure surface in turbid media | |
CN113793270A (en) | Aerial image geometric correction method based on unmanned aerial vehicle attitude information | |
CN111627073B (en) | Calibration method, calibration device and storage medium based on man-machine interaction | |
CN105374067A (en) | Three-dimensional reconstruction method based on PAL cameras and reconstruction system thereof | |
CN110274752A (en) | The Multifunctional test card and its test method of relay lens image quality | |
CN110136205B (en) | Parallax calibration method, device and system of multi-view camera | |
CN108917722B (en) | Vegetation coverage degree calculation method and device | |
CN107784633A (en) | Suitable for the unmanned plane image calibrating method of plane survey | |
CN111343360A (en) | Correction parameter obtaining method | |
CN112435303A (en) | Galvanometer system correction table construction method, construction system and galvanometer system correction method | |
CN112258581A (en) | On-site calibration method for multi-fish glasses head panoramic camera |
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 | ||
C17 | Cessation of patent right | ||
CF01 | Termination of patent right due to non-payment of annual fee |
Granted publication date: 20090527 Termination date: 20100314 |