CN104836953A - Multi-projector screen feature point automatic shooting and de-noising identification method - Google Patents
Multi-projector screen feature point automatic shooting and de-noising identification method Download PDFInfo
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- CN104836953A CN104836953A CN201510096168.1A CN201510096168A CN104836953A CN 104836953 A CN104836953 A CN 104836953A CN 201510096168 A CN201510096168 A CN 201510096168A CN 104836953 A CN104836953 A CN 104836953A
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Abstract
The present invention discloses a multi-projector screen feature point automatic shooting and de-noising identification method, comprising the steps of: fixing a camera onto a mechanical control device, automatically adjusting the position and a focal length of the camera, enabling the camera to directly face the center of a screen, so as to achieve automatic positioning, then using the camera to achieve shooting for all feature points of all projection screens, finally removing a public noise area, identifying the all feature points, establishing a mapping matrix from a camera space to a projector space, and operating a geometric correction algorithm by using projector coordinates of the feature points to perform geometric correction. The method of the present invention supports automatic positioning and shooting of the camera, and simultaneously recursively removes the public noise area of a picture in a feature point identifying process, thereby facilitating more accurate identifying of the feature points, eliminating noise interference, and improving and optimizing a final geometric correction result.
Description
Technical field
The present invention relates to Projection Display and technical field of image processing, particularly relate to a kind of multi-projector screen characteristics point automatic camera and denoising recognition methods.
Background technology
Along with the high speed development of science and technology and the rapid expansion of amount of information, at video display animation industry, numeral and virtual city and the numerous areas such as community, the design and planning, Automobile Design and Manufacturing, remote sensing and commander and extensive visualization in scientific computing, the requirement of people to Display Technique is also more and more higher.Owing to being subject to the restriction of display device resolution up till now, effectively cannot show oversize, high-resolution data.Wherein main demand is reflected in: high-resolution, super large physical size, feeling of immersion.Array of rear-projectors splice displaying system is the large screen display system be made up of multiple stage projecting apparatus and software or hardware image control unit.By the splicing of multiple stage projecting apparatus, the picture of high-resolution, high physical size, high brightness can be provided to export.Consider the many factors such as cost and feasibility, array of rear-projectors tiled display technology becomes a study hotspot received much concern.
Traditional separate unit display device has limitation in resolution and brightness, a solution relatively commonly used utilizes multiple stage display device array to carry out large-size screen monitors display, high-resolution is provided, but this technology has significantly splices gap, need to carry out geometric correction and edge fuses, a kind of technology wherein comprehensively uses camera and multi-projector, set up the mapping matrix between camera and projecting apparatus according to the characteristic point gathered simultaneously, then geometric correction is carried out, the weak point of this method implementation is, the position of camera may need the effect that manual adjustment just can reach optimum on the one hand, on the other hand in camera shooting process, ambient noise may have an impact to the identification of characteristic point, thus can not accurate recognition feature point, cause the last effect merged of rebuilding bad.
Summary of the invention
The object of the invention is to the deficiency for prior art, provide a kind of multi-projector screen characteristics point automatic camera and denoising recognition methods, the automation that the method realizes camera control is taken pictures; And characteristic point can be identified more accurately.
To achieve these goals, technical scheme provided by the invention is: provide a kind of multi-projector screen characteristics point automatic camera and denoising recognition methods, comprise the steps:
(1) machine control unit is placed in certain distance before projection screen array, and camera is fixed on machine control unit;
(2) theodolite in conjunction with projector projects white rectangle characteristic point to corresponding projection screen center, camera is taken pictures and is identified four angle points of white rectangle characteristic point, automatically camera position and focal length is adjusted according to result of calculation, make camera just to screen center, rectangular characteristic point occupies appropriate size on taking pictures, and realizes automatically locating;
(3) camera is located successfully automatically, gets a rectangular characteristic point on projection screen at regular intervals with theodolite, uses camera to automatically snap each characteristic point photo, until complete all characteristic point shootings of Current projection screen;
(4) repeat step (2) ~ (3), successively complete the characteristic point shooting of all projection screens;
(5) public noise region is removed, identify all characteristic points, the coordinate of characteristic point is transformed into Projector Space coordinate by camera coordinates, sets up the mapping matrix of camera space to Projector Space, run geometric correction algorithm by the projector coordinates of characteristic point and carry out geometric correction.
In above-mentioned steps (2), the method step that camera realizes location is automatically:
(2.1) identify the coordinate points of four angle points of white rectangle characteristic point, be respectively p
0, p
1, p
2, p
3;
(2.2) the centre coordinate point p of white rectangle characteristic point is calculated
4, the centre coordinate point p of photo
5, and rectangular block occupies whole photograph size ratio aspect:
p
4＝(p
0+p
3)/2,
p
5＝(picWidth+picHight)/2,
aspect＝blockArea/picArea，
Wherein, picWidth is film width, and picHight is photo height, and blockArea is white rectangle characteristic point footprint area on photograph, and picArea is the area of whole photograph;
(2.3) robot brain tool control device adjustment camera position, makes the centre coordinate point p of the rectangular characteristic point of calculating
4with the centre coordinate point p of photo
5overlap, guarantee that camera is invested and aim at screen center;
(2.4) adjust the focal length of camera, make rectangular block occupy whole photograph size ratio aspect and be in proper level, make rectangular characteristic point on taking pictures, occupy appropriate size.
In above-mentioned steps (5), the algorithm steps removing public noise region is:
(5.1) go out maximum category feature dot profile for often opening photo array, the centre coordinate calculating record i-th photo largest contours is Q
i;
(5.2) calculate the profile centre coordinate distance value of all photos corresponding to same projection screen, arranging predictive error threshold value is ε, if two coordinate centre-to-centre spacing distance values meet following decision condition:
Then judge that this profile is as public noise region, identifying this contour area in all photos is that public noise region is rejected;
(5.3) recurrence performs step (5.1) ~ (5.2), until often open the centre coordinate that photo all finds largest contours, and the centre coordinate distance value of profile is all greater than predetermined error threshold ε, then algorithm terminates, represent that often opening photo all have found different characteristic points, that is to say the characteristic point that will identify.
Preferably, above-mentioned machine control unit support moves up and down adjustment, thus realizes regulating the two-dimensional position of camera.
Preferably, all rectangular characteristic points that theodolite is got at regular intervals combine and have matrix chequered order feature, also namely have fixed lateral and longitudinal pitch between rectangular characteristic point.
Compared with prior art, multi-projector screen characteristics point automatic camera of the present invention and denoising recognition methods, support that camera is automatically located and takes pictures, avoid the tedious work manually adjusting camera position, realize the automation of camera control; Simultaneously in Feature point recognition process, the public noise region of removal picture of recurrence, contributes to identifying characteristic point more accurately, gets rid of noise jamming, promotes and optimizes final geometric correction result.
By following description also by reference to the accompanying drawings, the present invention will become more clear, and these accompanying drawings are for explaining embodiments of the invention.
Accompanying drawing explanation
Fig. 1 is the schematic flow sheet of embodiment of the present invention method.
Fig. 2 is the automatic location Calculation schematic diagram of embodiment of the present invention camera.
Embodiment
With reference now to accompanying drawing, describe embodiments of the invention, element numbers similar in accompanying drawing represents similar element.As mentioned above, as shown in Figure 1, a kind of multi-projector screen characteristics point automatic camera that the present embodiment provides and denoising recognition methods, comprise the steps:
S001 machine control unit is placed in certain distance before projection screen array, and camera is fixed on machine control unit;
S002 theodolite in conjunction with projector projects white rectangle characteristic point to corresponding projection screen center, camera is taken pictures and is identified four angle points of white rectangle characteristic point, automatically camera position and focal length is adjusted according to result of calculation, make camera just to screen center, rectangular characteristic point occupies appropriate size on taking pictures, and realizes automatically locating;
S003 camera is located successfully automatically, gets a rectangular characteristic point on projection screen at regular intervals with theodolite, uses camera to automatically snap each characteristic point photo, until complete all characteristic point shootings of Current projection screen;
S004 repeats step S002 ~ S003, successively completes the characteristic point shooting of all projection screens;
S005 removes public noise region, identify all characteristic points, the coordinate of characteristic point is transformed into Projector Space coordinate by camera coordinates, sets up the mapping matrix of camera space to Projector Space, run geometric correction algorithm by the projector coordinates of characteristic point and carry out geometric correction.
Shown in figure 1, label 101 represents that camera is taken pictures, and label 102 represents white rectangle characteristic point, illustrates in above-mentioned steps S002 with this figure, and the method that camera realizes location is automatically:
A1, identifies the coordinate points of four angle points of white rectangle characteristic point, is respectively p
0, p
1, p
2, p
3;
A2, calculates the centre coordinate point p of white rectangle characteristic point
4, the centre coordinate point p of photo
5, and rectangular block occupies whole photograph size ratio aspect:
p
4＝(p
0+p
3)/2,
p
5＝(picWidth+picHight)/2,
aspect＝blockArea/picArea，
Wherein, picWidth is film width, and picHight is photo height, and blockArea is white rectangle characteristic point footprint area on photograph, and picArea is the area of whole photograph;
A3 robot brain tool control device adjustment camera position, makes the centre coordinate point p of the rectangular characteristic point of calculating
4with the centre coordinate point p of photo
5overlap, guarantee that camera is invested and aim at screen center;
A4 adjusts the focal length of camera, makes rectangular block occupy whole photograph size ratio aspect and is in proper level, make rectangular characteristic point on taking pictures, occupy appropriate size.
In the present embodiment step S005, the algorithm steps removing public noise region is:
B1 goes out maximum category feature dot profile for often opening photo array, and the centre coordinate calculating record i-th photo largest contours is Q
i;
B2 calculates the profile centre coordinate distance value of all photos corresponding to same projection screen, and arranging predictive error threshold value is ε, if two coordinate centre-to-centre spacing distance values meet following decision condition:
Then judge that this profile is as public noise region, identifying this contour area in all photos is that public noise region is rejected;
B3 recurrence performs step B1 ~ B2, until often open the centre coordinate that photo all finds largest contours, and the centre coordinate distance value of profile is all greater than predetermined error threshold ε, then algorithm terminates, represent that often opening photo all have found different characteristic points, that is to say the characteristic point that will identify.
In detailed process, smaller public noise region may be there is time algorithm terminates, but this does not affect, because algorithm is found from largest contours diameter, time algorithm terminates, have found the characteristic point that will identify.In order to the efficiency improving algorithm need not wait the profile centre coordinate of all photos all to calculate to judge whether all equal in fact again, but n opens the center of the profile of photo before first calculating, if the profile center that the n calculated opens photo is all equal, directly judge that this contour area is public noise region and no longer goes for the profile center of n-th later picture.
In the present embodiment, above-mentioned machine control unit support moves up and down adjustment, thus realizes regulating the two-dimensional position of camera.
In the present embodiment, all rectangular characteristic points that theodolite is got at regular intervals combine and have matrix chequered order feature, also namely have fixed lateral and longitudinal pitch between rectangular characteristic point.
Compared with prior art, multi-projector screen characteristics point automatic camera of the present invention and denoising recognition methods, support that camera is automatically located and takes pictures, avoid the tedious work manually adjusting camera position, realize the automation of camera control; Simultaneously in Feature point recognition process, the public noise region of removal picture of recurrence, contributes to identifying characteristic point more accurately, gets rid of noise jamming, promotes and optimizes final geometric correction result.
Above disclosedly be only the preferred embodiments of the present invention, certainly can not limit the interest field of the present invention with this, therefore according to the equivalent variations that the present patent application the scope of the claims is done, still belong to the scope that the present invention is contained.
Claims (5)
1. multi-projector screen characteristics point automatic camera and a denoising recognition methods, is characterized in that, comprise the steps:
(1) machine control unit is placed in certain distance before projection screen array, and camera is fixed on machine control unit;
(2) theodolite in conjunction with projector projects white rectangle characteristic point to corresponding projection screen center, camera is taken pictures and is identified four angle points of white rectangle characteristic point, automatically camera position and focal length is adjusted according to result of calculation, make camera just to screen center, rectangular characteristic point occupies appropriate size on taking pictures, and realizes automatically locating;
(3) camera is located successfully automatically, gets a rectangular characteristic point on projection screen at regular intervals with theodolite, uses camera to automatically snap each characteristic point photo, until complete all characteristic point shootings of Current projection screen;
(4) repeat step (2) ~ (3), successively complete the characteristic point shooting of all projection screens;
(5) public noise region is removed, identify all characteristic points, the coordinate of characteristic point is transformed into Projector Space coordinate by camera coordinates, sets up the mapping matrix of camera space to Projector Space, run geometric correction algorithm by the projector coordinates of characteristic point and carry out geometric correction.
2. multi-projector screen characteristics point automatic camera as claimed in claim 1 and denoising recognition methods, is characterized in that, in step (2), the method step that camera realizes location is automatically:
(2.1) identify the coordinate points of four angle points of white rectangle characteristic point, be respectively p
0, p
1, p
2, p
3;
(2.2) the centre coordinate point p of white rectangle characteristic point is calculated
4, the centre coordinate point p of photo
5, and rectangular block occupies whole photograph size ratio aspect:
p
4＝(p
0+p
3)/2,
p
5＝(picWidth+picHight)/2,
aspect＝blockArea/picArea，
Wherein, picWidth is film width, and picHight is photo height, and blockArea is white rectangle characteristic point footprint area on photograph, and picArea is the area of whole photograph;
(2.3) robot brain tool control device adjustment camera position, makes the centre coordinate point p of the rectangular characteristic point of calculating
4with the centre coordinate point p of photo
5overlap, guarantee that camera is invested and aim at screen center;
(2.4) adjust the focal length of camera, make rectangular block occupy whole photograph size ratio aspect and be in proper level, make rectangular characteristic point on taking pictures, occupy appropriate size.
3. multi-projector screen characteristics point automatic camera and denoising recognition methods as claimed in claim 1, is characterized in that, in step (5), the algorithm steps removing public noise region is:
(5.1) go out maximum category feature dot profile for often opening photo array, the centre coordinate calculating record i-th photo largest contours is Q
i;
(5.2) calculate the profile centre coordinate distance value of all photos corresponding to same projection screen, arranging predictive error threshold value is ε, if two coordinate centre-to-centre spacing distance values meet following decision condition:
Then judge that this profile is as public noise region, identifying this contour area in all photos is that public noise region is rejected;
(5.3) recurrence performs step (5.1) ~ (5.2), until often open the centre coordinate that photo all finds largest contours, and the centre coordinate distance value of profile is all greater than predetermined error threshold ε, then algorithm terminates, represent that often opening photo all have found different characteristic points, that is to say the characteristic point that will identify.
4. multi-projector screen characteristics point automatic camera as claimed in claim 1 and denoising recognition methods, is characterized in that, described machine control unit support moves up and down adjustment, thus realization regulates the two-dimensional position of camera.
5. multi-projector screen characteristics point automatic camera as claimed in claim 1 and denoising recognition methods, it is characterized in that, in step (3), all rectangular characteristic points that theodolite is got at regular intervals combine and have matrix chequered order feature, also namely have fixed lateral and longitudinal pitch between rectangular characteristic point.
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|---|---|---|---|
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| CN104836953B CN104836953B (en) | 2019-01-15 |
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| CN106878680A (en) * | 2017-02-24 | 2017-06-20 | 深圳汇创联合自动化控制有限公司 | A kind of easy transmission facility recognition system |
| CN107105209A (en) * | 2017-05-22 | 2017-08-29 | 长春华懋科技有限公司 | Projected image geometric distortion automatic correction system and its bearing calibration |
| CN109889696A (en) * | 2019-03-18 | 2019-06-14 | 上海顺久电子科技有限公司 | Antinoise for automatic geometric correction shoots image-recognizing method and system |
| CN113497923A (en) * | 2020-03-18 | 2021-10-12 | 中强光电股份有限公司 | Projection system and positioning method for projection system |
| CN115314689A (en) * | 2022-08-05 | 2022-11-08 | 深圳海翼智新科技有限公司 | Projection correction method, projection correction device, projector and computer program product |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN113497923A (en) * | 2020-03-18 | 2021-10-12 | 中强光电股份有限公司 | Projection system and positioning method for projection system |
| CN113497923B (en) * | 2020-03-18 | 2023-10-31 | 中强光电股份有限公司 | Projection system and positioning method for projection system |
| CN115314689A (en) * | 2022-08-05 | 2022-11-08 | 深圳海翼智新科技有限公司 | Projection correction method, projection correction device, projector and computer program product |
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|---|---|
| CN104836953B (en) | 2019-01-15 |
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