CN102385750B - Line matching method and line matching system on basis of geometrical relationship - Google Patents
Line matching method and line matching system on basis of geometrical relationship Download PDFInfo
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- CN102385750B CN102385750B CN 201110169453 CN201110169453A CN102385750B CN 102385750 B CN102385750 B CN 102385750B CN 201110169453 CN201110169453 CN 201110169453 CN 201110169453 A CN201110169453 A CN 201110169453A CN 102385750 B CN102385750 B CN 102385750B
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Abstract
The invention discloses a line matching method and a line matching system on the basis of a geometrical relationship. The line matching method comprises the following steps of: a step 1 of carrying out line detection on a plurality of images; a step 2 of carrying out projection transformation on lines detected from the same image; a step 3 of obtaining an intersection point of circular arcs formed by the lines detected from the same image on a projection plane; a step 4 of generating a matching feature of the lines detected from the same image; and a step 5 of carrying out line matching by the matching features corresponding to the lines detected from each image. In the method, a fundamental matrix does not need to be obtained in advanced, the influence of the point matching precision on the precision of the line matching is avoided, and the efficiency of a matching algorithm is improved.
Description
Technical field
The present invention relates to image processing field, relate in particular to straight line matching process and system based on geometric relationship.
Background technology
Straight line is to constitute important geometric element in the object in the three-dimensional world.The linear feature of object still keeps in the two dimensional image that obtains from three-dimensional scenic.In the image of under the different visual angles Same Scene being taken a part of straight line remain unchanged or straight line between have certain correlativity, find the straight line of the correspondence in the different images, utilize the corresponding relation between the straight line to determine that coupling and transformation relation between two width of cloth images have important meaning.The recovery of three-dimensional scenic mainly utilizes a little and line comes out the reproductions such as object target of three-dimensional, and the straight line in the coupling different images is the important foundation of three-dimensional reconstruction.
The method of straight line coupling mainly adopts utmost point geometrical constraint to carry out coupling just, and the recycling correlation method carries out the essence coupling.Utmost point geometrical constraint method is to utilize the geometric relationship of the image that obtains under two visual angles, set up the corresponding geometric transformation relation between picture point, the geometrical constraint of point in the image at another visual angle in piece image can be represented by fundamental matrix, the fundamental matrix that obtains between image utilizes two end points of straight line can obtain the zone of meeting geometric constraint in another visual angle image, belong to the regional straight line of geometrical constraint as candidate's straight line, finish thick coupling.Smart coupling adopts relevant method, and the grey scale change of choosing pixel in the straight line neighborhood realizes coupling as similarity.
Adopt the method for utmost point geometrical constraint need ask for fundamental matrix in advance, asking for of fundamental matrix is to adopt match point that the method for asking linear equation is realized, before the straight line coupling, need to carry out a coupling, the precision receptor site matching precision influence of straight line coupling, matching algorithm efficiency is not high.
Summary of the invention
At the above-mentioned problems in the prior art, the invention provides straight line matching process and system based on geometric relationship.
The invention provides the straight line matching process based on geometric relationship, comprising:
Step 1 is carried out straight-line detection to several images;
Step 2, to from same image detection to straight line carry out projective transformation;
Step 3, ask for same image detection to the intersection point of the circular arc that forms on the projecting plane of straight line;
Step 4 generates the matching characteristic of the straight line that same image detection arrives;
In one example, in the step 1, thereby edge of image detected the straight line that detects in the image.
In one example, in the step 2, with image
Geometric center as the central point of coordinate transform, projection centre is the central point of unit sphere, wherein L
1, L
2, L
3..., L
nBe detected straight line in the same image.
In one example, in the step 2, establishing the coordinate of coordinate transform central point in image is (q
X0q
Y0), in the same image on the detected straight line coordinate of any point be (q
xq
y), then The Transformation Relation of Projection is:
In one example, in the step 3, establish on first circular arc of detected two straight line correspondences in the same image and 2 coordinate vector on second circular arc is respectively
With
Then the intersection point of circular arc is
In one example, step 4 comprises:
Step 41 is chosen the corresponding distance between two points on straight line of the intersection point coordinate points p farthest of camber line
Max1, p
Max2, and with its mid point
As new coordinate transform central point, and detected straight line in the same image carried out new projective transformation;
Be coordinate points p
Max1, p
Max2At the mid point of X-axis,
Be coordinate points p
Max1, p
Max2Mid point in Y-axis;
Step 42 is asked for coordinate points p
Max1, p
Max2The unit normal vector of place circular arc under new projection, and this unit normal vector is set to reference vector;
Step 43, the intersection point that calculates detected straight line in the same image under new projection coordinate vector and the angle of reference vector;
Step 44 sorts the back as the matching characteristic of straight line with angle.
In one example, in the step 5, utilize nearest criterion that the matching characteristic of straight line is mated.
The invention provides a kind of system that realizes based on the straight line matching process of geometric relationship.
The present invention need not to ask in advance fundamental matrix, has avoided the influence of some matching precision to the precision of straight line coupling, has improved the efficient of matching algorithm.
Description of drawings
Come the present invention is described in further detail below in conjunction with accompanying drawing, wherein:
Fig. 1 is the straight line matching process process flow diagram based on geometric relationship of the present invention;
Fig. 2 is the projective transformation illustraton of model;
Fig. 3 is that the circular arc intersection point is asked for schematic diagram.
Embodiment
The present invention proposes a kind of new straight line matching process, utilize the geometric relationship between the image cathetus to carry out matching judgment.Have parallel and overlapping relation between straight line in the image and the straight line, crossing or parallel relation between the image straight line that obtains under the different visual angles is constant under certain condition, determine the geometric relationship of straight line and other straight lines from straight line, utilize whether a straightforward differentiation of geometric relationship is same straight line.After linear projection is to the sphere, there are two intersection points in per two straight lines at sphere, this two intersection point is two limits of sphere great circle, choose limit as the expression amount of geometric relationship, with the geometric relationship employing vector representation of each bar straight line with other straight lines, utilize vector correlation to mate as matching criterior.
Method provided by the invention as shown in Figure 1, it has used 2 images (being not limited to 2 images), i.e. image 1 and image 2, but identical to each treatment of picture flow process.Method provided by the invention comprises:
Two intersection points are about centre of sphere symmetry, and amount of orientation first component is not less than zero value and is designated as
Obtain other circular arcs together
The intersection point of projection circular arc,
At ∏
1On corresponding point
In like manner ask for the intersection point between each circular arc successively, i.e. image ∏
1Cathetus
With
The intersection point of projection circular arc is
Corresponding point in original image are
Account for
Coordinate vector at the subpoint of newly casting:
The unit normal vector of crossing these 2 circular arcs is:
Note
Be reference vector
Each intersection point projection coordinate vector is with the angle of reference vector:
Right
Sort by size the result
Then matching characteristic is expressed as:
Claims (3)
1. based on the straight line matching process of geometric relationship, it is characterized in that, comprising:
Step 1 is carried out straight-line detection to several images;
Step 2, to from same image detection to straight line carry out projective transformation, wherein, with image
Geometric center as the central point of coordinate transform, projection centre is the central point of unit sphere, wherein L
1, L
2, L
3..., L
nBe detected straight line in the same image, establishing the coordinate of coordinate transform central point in image is (q
X0q
Y0), in the same image on the detected straight line coordinate of any point be (q
xq
y), then The Transformation Relation of Projection is:
Step 3, ask for same image detection to the intersection point of the circular arc that forms on the projecting plane of straight line, establish on first circular arc of detected two straight line correspondences in the same image and 2 coordinate vector on second circular arc is respectively
With
Then the intersection point of circular arc is
Step 4 generates the matching characteristic of the straight line that same image detection arrives, and is in described step 4, further comprising the steps of:
Step 41 is chosen the corresponding distance between two points on straight line of the intersection point coordinate points p farthest of camber line
Max1, p
Max2, and with described coordinate points p farthest
Max1, p
Max2Mid point
As new coordinate transform central point, and detected straight line in the same image carried out new projective transformation;
Be coordinate points p
Max1, p
Max2At the mid point of X-axis,
Be coordinate points p
Max1, p
Max2Mid point in Y-axis;
Step 42 is asked for coordinate points p
Max1, p
Max2The unit normal vector of place circular arc under new projection, and this unit normal vector is set to reference vector;
Step 43, calculate detected straight-line intersection in the same image under new projection coordinate vector and the angle of reference vector;
Step 44 sorts the back as the matching characteristic of straight line with angle;
Step 5, utilize from each image detection to the matching characteristic of straight line correspondence carry out the straight line coupling.
2. the straight line matching process based on geometric relationship as claimed in claim 1 is characterized in that, in the step 1, thereby edge of image is detected the straight line that detects in the image.
3. the straight line matching process based on geometric relationship as claimed in claim 1 or 2 is characterized in that, in the step 5, utilizes nearest criterion that the matching characteristic of straight line is mated.
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CN103345642B (en) * | 2013-06-28 | 2016-05-25 | 华中科技大学 | A kind of image matching method based on dotted line antithesis |
CN106296645A (en) * | 2015-06-25 | 2017-01-04 | 株式会社理光 | Image processing method and image processing apparatus |
CN105160311B (en) * | 2015-08-26 | 2018-08-28 | 清华大学 | Algorism of Matching Line Segments method and device |
CN106934788B (en) * | 2015-12-30 | 2020-11-24 | 中国科学院沈阳自动化研究所 | Rapid extraction method of straight line inclination angle |
CN105719309B (en) * | 2016-01-27 | 2018-08-14 | 大连理工大学 | A kind of matching line segments method based on projective invariant |
CN107480710B (en) * | 2017-08-01 | 2020-05-22 | 歌尔股份有限公司 | Feature point matching result processing method and device |
CN109064440B (en) * | 2018-06-19 | 2022-02-22 | 广东工业大学 | Loudspeaker voice coil bonding wire identification method based on machine vision |
Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
EP1277079B1 (en) * | 2000-04-25 | 2006-03-29 | Rodenstock GmbH | Method for calculating a progressive spectacle lens and method for producing a spectacle lens of this type |
CN1941850A (en) * | 2005-09-29 | 2007-04-04 | 中国科学院自动化研究所 | Pedestrian tracting method based on principal axis marriage under multiple vedio cameras |
CN101561269A (en) * | 2009-05-26 | 2009-10-21 | 张征宇 | Method for automatically matching characteristic lines of close-range photogrammetry |
CN101621711A (en) * | 2009-07-23 | 2010-01-06 | 东南大学 | Method for calibrating camera by adopting two same circles |
CN101862177A (en) * | 2010-04-20 | 2010-10-20 | 中山大学中山眼科中心 | Method and device for three-dimensionally positioning retinal hole |
-
2011
- 2011-06-22 CN CN 201110169453 patent/CN102385750B/en active Active
Patent Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
EP1277079B1 (en) * | 2000-04-25 | 2006-03-29 | Rodenstock GmbH | Method for calculating a progressive spectacle lens and method for producing a spectacle lens of this type |
CN1941850A (en) * | 2005-09-29 | 2007-04-04 | 中国科学院自动化研究所 | Pedestrian tracting method based on principal axis marriage under multiple vedio cameras |
CN101561269A (en) * | 2009-05-26 | 2009-10-21 | 张征宇 | Method for automatically matching characteristic lines of close-range photogrammetry |
CN101621711A (en) * | 2009-07-23 | 2010-01-06 | 东南大学 | Method for calibrating camera by adopting two same circles |
CN101862177A (en) * | 2010-04-20 | 2010-10-20 | 中山大学中山眼科中心 | Method and device for three-dimensionally positioning retinal hole |
Non-Patent Citations (2)
Title |
---|
一种基于特征编组的直线立体匹配全局算法;文贡坚;《软件学报》;20061231;第17卷(第12期);2471-2484 * |
文贡坚.一种基于特征编组的直线立体匹配全局算法.《软件学报》.2006,第17卷(第12期),2471-2484. |
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