CN107993197A - The joining method and system of a kind of panorama camera - Google Patents
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Abstract
It the invention discloses the joining method and system of a kind of panorama camera, the described method comprises the following steps, obtain the image of several imaging sensors and be buffered in the built-in storage of panorama camera；The adjacent two images in left and right are chosen out of built-in storage to be spliced, and matched window area is determined using the algorithm of Window match；The required rotation of image mosaic, translation matrix are calculated by matched pixel point coordinates, and rotates, translate two images；Left images are subjected to pixel fusion, realize image mosaic.The joining method and system of a kind of panorama camera provided by the invention are chosen the adjacent two images in left and right from the built-in storage of panorama camera by the USB3.0 data transmission interfaces of panorama camera and are spliced, and matched window area in two width figures is found using the algorithm of Window match；This matching process can effectively reduce matched search area and calculation times, have the computational efficiency of higher, be easy to implement the real-time splicing of image.
Description
Technical field
The invention belongs to Panorama Mosaic technical field, is specifically a kind of joining method of panorama camera and is
System.
Background technology
Panorama camera has been widely used in the fields such as robot, virtual reality, and main implementation is using special
Imaging sensor obtains image and view data is transferred to the smart machines such as computer or mobile phone, the processor fortune of smart machine
Row merging algorithm for images realizes the splicing of panoramic picture, and such framework depends on the disposal ability of smart machine, image is spelled
The real-time deficiency connect, influences the fluency of panorama；Secondly, existing panorama camera largely uses two wide angle cameras
Scheme realize the acquisitions of 360 degree of images, the distortion of image is larger, influences imaging effect.
The content of the invention
The technical problems to be solved by the invention, which are to provide one kind, can in real time correct and splice and can realize 360 degree
The joining method and system of the good panorama camera of image acquisition imaging effect.
In view of the deficiencies of the prior art, the present invention intends to provide a kind of joining method of panorama camera and be
System.
To achieve the above object, the present invention provides following technical solution：
A kind of joining method of panorama camera, the described method comprises the following steps,
Step S01:Obtain the image of several imaging sensors and be buffered in the built-in storage of panorama camera；
Step S02:Choose the adjacent two images in left and right out of panorama camera built-in storage to be spliced, using window
The algorithm matched somebody with somebody determines matched window area in two width figures；
Step S03:The required rotation of image mosaic, translation matrix are calculated by matched pixel point coordinates, and rotate,
Translate two images；
Step S04:Left images are subjected to pixel fusion, realize image mosaic.
Further, described image splicing realizes image by using the image mosaic module designed on FPGA processor
Stitching algorithm, realizes Panorama Mosaic.
Further, the algorithm of Window match is to realize pixel between the adjacent two images in left and right using the matching way of SAD
Matching, by the preliminary screening of SAD algorithms, find the window being mutually matched in left images, the algorithmic notation of Window match
For:
Wherein x1And x2The conjunction of pixel value in the correspondence window of two width figures of left and right is represented respectively.
Further, the splicing speed of described image concatenation module is synchronous with the acquisition speed of imaging sensor.
Further, the relation in the step S02 between the adjacent two images in left and right is expressed as with matrix H：
Wherein, X1For the character pixel point coordinates in image, X2For matching of this feature pixel in another plane of delineation
Pixel；H0, h1, h2, h3, h4, h5, h6, h7, h8 are nine elements of matrix H.
When the rotation angle between two pictures to be spliced is less than 30 °, and camera plane and scenery holding in the step S03
To under conditions of vertical, the coordinate transformation relation between two width pictures, affine Transform Model are represented using affine Transform Model
It is expressed as：
Wherein, x, y represent the image coordinate before conversion, the transformed image coordinate of x ', y ' expression；A, b represent two phases
The parameter converted between machine plane, 6 ginsengs in formula can be tried to achieve by choosing 6 groups of corresponding matching characteristic points and bringing its positional information into
Several estimates.
Further, pixel fusion is realized using the method for weighted average in the step S04, it is different by selecting
Weighted value w1And w2The rate of specific gravity shared by the image pixel of fused image Central Plains can be adjusted, the algorithm of weighted average is：
F (x, y)=w1f1(x, y)+w2f2(x, y)；(x, y) ∈ (f1∩f2)
Wherein, the coordinate position on x, y representative image sensor, f1(x, y) represents target pixel points left pixel point
Pixel value, f2(x, y) represents the pixel value of target pixel points right pixel point, and f (x, y) represents the pixel value of target pixel points.
Further, the weighted value can be allocated by pixel distribution situation, gradual from center picture to edge
Reduce the weighted value of pixel；Image wherein after adjustment fusion is identical with the resolution ratio of original image.
In the example of the present invention, there is provided a kind of splicing system of panorama camera, including：
Image collection module, for obtaining sensor image and being buffered in the built-in storage of panorama camera；
Window match module, for determining matched window area in the adjacent two width figure in left and right；
Images match module, for calculating the required rotation of image mosaic, translation matrix, and rotates, translates two width
Image；
Image co-registration module, merges for image pixel, realizes image mosaic.
Compared with prior art the beneficial effects of the invention are as follows：
First, the present invention chooses a left side by the USB3.0 data transmission interfaces of panorama camera from the built-in storage of panorama camera
Right adjacent two images are spliced, and are usedThe algorithm of Window match determines matched window area in two width figures；
It is this that matched search area and calculation times can be effectively reduced using local matching process, the calculating for having higher
Efficiency, be easy to implement real-time stitching algorithm.
2nd, the polyphaser robot platform based on FPGA that we design in the present invention devises 360 degree of panorama phases
Machine system, picture is obtained by being looped around multiple cameras near the type heart, using it is proposed that the panorama based on FPGA platform
Robot vision platform, accelerates SIFT Robust Algorithm of Image Corner Extraction by FPGA, realize realizes SIFT angles in hardware platform
The detection and matching of point.Again use it is proposed that the images match and stitching algorithm based on FPGA, finally realize panorama machine
The real-time splicing of device human visual system's image.
3rd, the present invention utilizes the image high-performance treatments of FPGA platform, we are realized using the SIFT feature detected
The coincidence splicing of two width pictures.The splicing effect of picture entirety is excellent, does not splice trace, the geometrical relationship of picture significantly
Can also accurately it be rebuild；In addition the splicing that we are carried out using the weighted mean method two width pictures adjacent to left and right,
It can be found that can realize smoother transition in seam crossing, obvious lofty sense is not had.
Brief description of the drawings
Fig. 1 is the flow diagram of the joining method of the panorama camera of one embodiment of the invention；
Fig. 2 is the structure diagram of the splicing system of the panorama camera of one embodiment of the invention.
Embodiment
The invention will be further described below in conjunction with the accompanying drawings：
Referring to Fig. 1, Fig. 1 is a kind of flow of the joining method embodiment of panorama camera disclosed by the embodiments of the present invention
Schematic diagram.As shown in Figure 1, a kind of joining method of panorama camera, the described method comprises the following steps,
Step S01:Obtain the image of several imaging sensors and be buffered in the built-in storage of panorama camera；
Step S02:Choose the adjacent two images in left and right out of panorama camera built-in storage to be spliced, using window
The algorithm matched somebody with somebody determines matched window area in two width figures；
Step S03:The required rotation of image mosaic, translation matrix are calculated by matched pixel point coordinates, and rotate,
Translate two images；
Step S04:Left images are subjected to pixel fusion, realize image mosaic.
Described image splicing realizes merging algorithm for images by using the image mosaic module designed on FPGA processor,
Realize Panorama Mosaic.
The algorithm of Window match is the matching that pixel between the adjacent two images in left and right is realized using the matching way of SAD, is passed through
The preliminary screening of SAD algorithms is crossed, finds the window being mutually matched in left images, the algorithmic notation of Window match is:
Wherein x1And x2The conjunction of pixel value in the correspondence window of two width figures of left and right is represented respectively.
The splicing speed of described image concatenation module is synchronous with the acquisition speed of imaging sensor.
Relation in the step S02 between the adjacent two images in left and right is expressed as with matrix H：
Wherein, X1For the character pixel point coordinates in image, X2For matching of this feature pixel in another plane of delineation
Pixel；H0, h1, h2, h3, h4, h5, h6, h7, h8 are nine elements of matrix H.
When the rotation angle between two pictures to be spliced is less than 30 °, and camera plane and scenery holding in the step S03
Under conditions of vertical, the coordinate transformation relation between two width pictures, affine Transform Model table are represented using affine Transform Model
It is shown as：
Wherein, x, y represent the image coordinate before conversion, the transformed image coordinate of x ', y ' expression；A, b represent two phases
The parameter converted between machine plane, 6 ginsengs in formula can be tried to achieve by choosing 6 groups of corresponding matching characteristic points and bringing its positional information into
Several estimate, so as to try to achieve affine transformation relationship between two width pictures.In image co-registration, the design is using weighted average
Method realizes more preferably image co-registration.
The coordinate transformation relation mainly includes：Rotation transformation, translation transformation and size scaling conversion.
Pixel fusion is realized using the method for weighted average in the step S04, by selecting different weighted value w1
And w2The rate of specific gravity shared by the image pixel of fused image Central Plains can be adjusted, the algorithm of weighted average is：
F (x, y)=w1f1(x, y)+w2f2(x, y)；(x, y) ∈ (f1∩f2)
Wherein, the coordinate position on x, y representative image sensor, f1(x, y) represents target pixel points left pixel point
Pixel value, f2(x, y) represents the pixel value of target pixel points right pixel point, and f (x, y) represents the pixel value of target pixel points.
Further, the weighted value can be allocated by pixel distribution situation, gradual from center picture to edge
Reduce the weighted value of pixel；Image wherein after adjustment fusion is identical with the resolution ratio of original image.
Referring to Fig. 2, Fig. 2 is a kind of flow of the joining method embodiment of panorama camera disclosed by the embodiments of the present invention
Schematic diagram.As shown in Fig. 2, a kind of splicing system of panorama camera, including：Image collection module 10, for obtaining sensor map
Picture is simultaneously buffered in the built-in storage of panorama camera；
Window match module 20, for determining matched window area in the adjacent two width figure in left and right；
Images match module 30, for calculating the required rotation of image mosaic, translation matrix, and rotates, translates two
Width image；
Image co-registration module 40, merges for image pixel, realizes image mosaic.
Main feature, application method, basic principle and the advantages of the present invention of the present invention has been shown and described above.This
Industry technology personnel are it should be appreciated that the present invention is not limited to the above embodiments, described in the above embodiment and specification
It is to illustrate the principle of the present invention, without departing from the spirit and scope of the present invention, the present invention can also have according to actual conditions
Various changes and modifications, these changes and improvements all fall within the protetion scope of the claimed invention.The claimed scope of the invention
It is defined by the appending claims and its equivalent thereof.
Claims (9)
- A kind of 1. joining method of panorama camera, it is characterised in that it the described method comprises the following steps,Step S01:Obtain the image of several imaging sensors and be buffered in the built-in storage of panorama camera；Step S02:Choose the adjacent two images in left and right out of panorama camera built-in storage to be spliced, using Window match Algorithm determines matched window area in two width figures；Step S03:The required rotation of image mosaic, translation matrix are calculated by matched pixel point coordinates, and rotates, translate Two images；Step S04:Left images are subjected to pixel fusion, realize image mosaic.
- 2. the joining method of panorama camera according to claim 1, it is characterised in that described image is spliced by FPGA The image mosaic module designed on reason device realizes merging algorithm for images, realizes Panorama Mosaic.
- 3. the joining method of panorama camera according to claim 1, it is characterised in that the algorithm of Window match is to use SAD Matching way realize the matching of pixel between the adjacent two images in left and right, by the preliminary screening of SAD algorithms, find left images In the window that is mutually matched, the algorithmic notation of Window match is:<mrow> <mi>S</mi> <mi>A</mi> <mi>D</mi> <mo>=</mo> <mfenced open = "{" close = ""> <mtable> <mtr> <mtd> <mrow> <msub> <mi>x</mi> <mn>1</mn> </msub> <mo>-</mo> <msub> <mi>x</mi> <mn>2</mn> </msub> <mo>,</mo> <msub> <mi>x</mi> <mn>1</mn> </msub> <mo>></mo> <msub> <mi>x</mi> <mn>2</mn> </msub> </mrow> </mtd> </mtr> <mtr> <mtd> <mrow> <msub> <mi>x</mi> <mn>2</mn> </msub> <mo>-</mo> <msub> <mi>x</mi> <mn>1</mn> </msub> <mo>,</mo> <msub> <mi>x</mi> <mn>1</mn> </msub> <mo><</mo> <msub> <mi>x</mi> <mn>2</mn> </msub> </mrow> </mtd> </mtr> <mtr> <mtd> <mrow> <mn>0</mn> <mo>,</mo> <msub> <mi>x</mi> <mn>1</mn> </msub> <mo>=</mo> <msub> <mi>x</mi> <mn>2</mn> </msub> </mrow> </mtd> </mtr> </mtable> </mfenced> <mo>;</mo> </mrow>Wherein x1And x2The conjunction of pixel value in the correspondence window of two width figures of left and right is represented respectively.
- 4. the joining method of panorama camera according to claim 1, it is characterised in that the splicing speed of described image concatenation module Degree is synchronous with the acquisition speed of imaging sensor.
- 5. the joining method of panorama camera according to claim 1, it is characterised in that left and right adjacent two in the step S02 Relation between width image is expressed as with matrix H：<mrow> <msub> <mi>X</mi> <mn>1</mn> </msub> <mo>=</mo> <msub> <mi>HX</mi> <mn>2</mn> </msub> <mo>,</mo> <mi>H</mi> <mo>=</mo> <mfenced open = "[" close = "]"> <mtable> <mtr> <mtd> <msub> <mi>h</mi> <mn>0</mn> </msub> </mtd> <mtd> <msub> <mi>h</mi> <mn>1</mn> </msub> </mtd> <mtd> <msub> <mi>h</mi> <mn>2</mn> </msub> </mtd> </mtr> <mtr> <mtd> <msub> <mi>h</mi> <mn>3</mn> </msub> </mtd> <mtd> <msub> <mi>h</mi> <mn>4</mn> </msub> </mtd> <mtd> <msub> <mi>h</mi> <mn>5</mn> </msub> </mtd> </mtr> <mtr> <mtd> <msub> <mi>h</mi> <mn>6</mn> </msub> </mtd> <mtd> <msub> <mi>h</mi> <mn>7</mn> </msub> </mtd> <mtd> <msub> <mi>h</mi> <mn>8</mn> </msub> </mtd> </mtr> </mtable> </mfenced> <mo>;</mo> </mrow>Wherein, X1For the character pixel point coordinates in image, X2For matched pixel of this feature pixel in another plane of delineation Point；H0, h1, h2, h3, h4, h5, h6, h7, h8 are nine elements of matrix H.
- 6. the joining method of panorama camera according to claim 1, it is characterised in that when two width are waited to spell in the step S03 Under conditions of rotation angle between map interlinking piece is less than 30 °, and camera plane is vertical with scenery, represented using affine Transform Model Coordinate transformation relation between two width pictures, affine Transform Model are expressed as：<mrow> <mfenced open = "[" close = "]"> <mtable> <mtr> <mtd> <msup> <mi>x</mi> <mo>&prime;</mo> </msup> </mtd> </mtr> <mtr> <mtd> <msup> <mi>y</mi> <mo>&prime;</mo> </msup> </mtd> </mtr> </mtable> </mfenced> <mo>=</mo> <msub> <mfenced open = "[" close = "]"> <mtable> <mtr> <mtd> <mrow> <msub> <mi>a</mi> <mn>11</mn> </msub> <mi>x</mi> <mo>+</mo> <msub> <mi>a</mi> <mn>12</mn> </msub> <mi>y</mi> <mo>+</mo> <msub> <mi>b</mi> <mn>1</mn> </msub> </mrow> </mtd> </mtr> <mtr> <mtd> <mrow> <msub> <mi>a</mi> <mn>21</mn> </msub> <mi>x</mi> <mo>+</mo> <msub> <mi>a</mi> <mn>22</mn> </msub> <mi>y</mi> <mo>+</mo> <msub> <mi>b</mi> <mn>2</mn> </msub> </mrow> </mtd> </mtr> </mtable> </mfenced> <mrow> <mn>2</mn> <mi>x</mi> <mn>3</mn> </mrow> </msub> <mo>;</mo> </mrow>Wherein, x, y represent the image coordinate before conversion, the transformed image coordinate of x ', y ' expression；A, b represent two cameras and put down The parameter converted between face, 6 parameters can be tried to achieve in formula by choosing 6 groups of corresponding matching characteristic points and bring its positional information into Estimate.
- 7. the joining method of panorama camera according to claim 1, it is characterised in that flat using weighting in the step S04 The method of average realizes pixel fusion, by selecting different weighted value w1And w2Fused image Central Plains image slices can be adjusted Rate of specific gravity shared by element, the algorithm of weighted average are：<mrow> <msub> <mi>w</mi> <mn>1</mn> </msub> <mrow> <mo>(</mo> <mi>x</mi> <mo>,</mo> <mi>y</mi> <mo>)</mo> </mrow> <mo>=</mo> <mrow> <mo>(</mo> <mn>1</mn> <mo>-</mo> <mo>|</mo> <mfrac> <mi>x</mi> <mrow> <mi>w</mi> <mi>i</mi> <mi>d</mi> <mi>t</mi> <mi>h</mi> </mrow> </mfrac> <mo>-</mo> <mn>0.5</mn> <mo>|</mo> <mo>)</mo> </mrow> <mo>,</mo> <msub> <mi>w</mi> <mn>2</mn> </msub> <mrow> <mo>(</mo> <mi>x</mi> <mo>,</mo> <mi>y</mi> <mo>)</mo> </mrow> <mo>=</mo> <mrow> <mo>(</mo> <mn>1</mn> <mo>-</mo> <mo>|</mo> <mfrac> <mi>x</mi> <mrow> <mi>h</mi> <mi>e</mi> <mi>i</mi> <mi>g</mi> <mi>h</mi> <mi>t</mi> </mrow> </mfrac> <mo>-</mo> <mn>0.5</mn> <mo>|</mo> <mo>)</mo> </mrow> <mo>;</mo> </mrow>F (x, y)=w1f1(x, y)+w2f2(x, y)；(x, y) ∈ (f1∩f2)；Wherein, the coordinate position on x, y representative image sensor, f1(x, y) represents the pixel of target pixel points left pixel point Value, f2(x, y) represents the pixel value of target pixel points right pixel point, and f (x, y) represents the pixel value of target pixel points.
- 8. the joining method of panorama camera according to claim 7, it is characterised in that the weighted value can pass through pixel point Cloth situation is allocated, and the weighted value of pixel is gradually reduced from center picture to edge；Image and original wherein after adjustment fusion The resolution ratio of image is identical.
- A kind of 9. splicing system of panorama camera, it is characterised in that including：Image collection module, for obtaining sensor image and being buffered in the built-in storage of panorama camera；Window match module, for determining matched window area in the adjacent two width figure in left and right；Images match module, for calculating the required rotation of image mosaic, translation matrix, and rotates, translates two images；Image co-registration module, merges for image pixel, realizes image mosaic.
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| CN108986183B (en) * | 2018-07-18 | 2022-12-27 | 合肥亿图网络科技有限公司 | Method for manufacturing panoramic map |
| CN109166078A (en) * | 2018-10-22 | 2019-01-08 | 广州微牌智能科技有限公司 | Panoramic view joining method, device, viewing system, equipment and storage medium |
| CN112511767A (en) * | 2020-10-30 | 2021-03-16 | 济南浪潮高新科技投资发展有限公司 | Video splicing method and device, and storage medium |
| CN112511767B (en) * | 2020-10-30 | 2022-08-02 | 山东浪潮科学研究院有限公司 | Video splicing method and device, and storage medium |
| CN113112404A (en) * | 2021-04-02 | 2021-07-13 | 广州图匠数据科技有限公司 | Image splicing method and device based on sliding window |
| CN113850905A (en) * | 2021-09-29 | 2021-12-28 | 中国科学院长春光学精密机械与物理研究所 | Panoramic image real-time splicing method for circumferential scanning type photoelectric early warning system |
| CN113850905B (en) * | 2021-09-29 | 2024-04-12 | 中国科学院长春光学精密机械与物理研究所 | Panoramic image real-time stitching method for circumferential scanning type photoelectric early warning system |
| CN114332078A (en) * | 2022-03-02 | 2022-04-12 | 山东华硕汽车配件科技有限公司 | Intelligent repair control method for metal abrasion of automobile engine |
| CN114332078B (en) * | 2022-03-02 | 2022-06-10 | 山东华硕汽车配件科技有限公司 | Intelligent repair control method for metal abrasion of automobile engine |
| CN115620154B (en) * | 2022-12-19 | 2023-03-07 | 江苏星湖科技有限公司 | Panoramic map superposition replacement method and system |
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