CN102184536A - Method and system for extracting straight line and/or line segment end points from image - Google Patents
Method and system for extracting straight line and/or line segment end points from image Download PDFInfo
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Abstract
The invention relates to a method and a system for extracting straight line and/or line segment end points from an image. The method comprises the following steps of: 1, performing spherical projection on the image; 2, extracting a circular arc from the large circle of a spherical surface; and 3, acquiring a straight line equation and/or the line segment end points by using the circular arc. The technical scheme provided by the invention is simple and practicable and high in noise resisting capability, and straight line parameters and/or the straight line end points can be detected at the same time.
Description
Technical field
The present invention relates to digital image processing field, relate in particular to a kind of image cathetus and extract and extremity of segment point detecting method and system.
Background technology
Straight-line detection is widely used in computer vision and the Flame Image Process, such as target registration, target following and Target Recognition.Image packets for the interior of building outside contains a large amount of straight line information, and the information of straight line has important scientific research value and practical significance for the three-dimensional reconstruction of scene under the detection of straight lines acquisition different visual angles.Straight-line detection be used in take photo by plane or remote sensing images in the bridge, road, river, shore line, airfield runway, local horizon, buildings rim detection, and be applied in the Road Detection of vehicle-mounted autonomous navigation system.
Take photo by plane airfield runway in the image, local horizon detects in the middle of the independent landing navigation that is mainly used in aircraft, in the area image of aircraft camera place information such as local horizon and airfield runway are arranged, local horizon and position and the form of airfield runway in image can change when attitude of flight vehicle changed, determine to change corresponding relation between the two, thereby utilize local horizon and the airfield runway position form in image to find the solution the automatic navigation control that attitude of flight vehicle is realized aircraft.The image information of obtaining based on the intelligent vehicle autonomous navigation system of vision is the road information of its traffic direction, determines that by the edge of road in the detected image position of vehicle in road come the course angle of analytical calculation vehicle to realize Autonomous Control.Contain in airfield runway, local horizon, the road image, between zone such as runway, local horizon, road and the peripheral region edge feature is arranged, these edges mostly are linear feature, finish the method that detection need be adopted straight-line detection.
The method of straight-line detection mainly contains two classes: based on the straight-line detection of Hough (Hough) conversion with based on the straight-line detection of chain code.
Hough conversion basic thought is to utilize a little---the line antithesis, with the satisfied equation of constraint of point on the image space straight line, become parametric form, at the line that the some correspondence in the image space intersects in parameter space, the Hough conversion utilizes this relation the straight-line detection problem to be become the problem of asking extreme value in the parameter space.The Hough transform method is simple, even and straight line has the parameter of interruption also can detect, but exist the end points and the length information that can not obtain the image middle conductor, calculated amount is big, becomes problem such as big because the straight line parameter that the evaluated error that parameter space resolution is introduced calculates is determined the point on the straight line with the increase of straight length.Having on the basis of Hough conversion from improving improved method on its computing velocity, the method that adopts contrary Hough conversion is arranged, but these methods can not well solve the problem of fast detecting straight line parameter and line segment end points.The straight line parameter that the evaluated error that parameter space resolution is introduced calculates determines that the point on the straight line becomes big problem with the increase of straight length, does not also have effective ground method to solve.
Chain code is that the position relation of 8 of neighborhoods a bit and on every side in the image adopts coded representation.Point represents to present certain rules with the chain code sequence on the straight line, and this rule is freeman (Freeman) criterion.Straight-line detection based on chain code obtains a series of chain code sequences of image exactly, and the sequence that meets the Freeman criterion is a straight line.The Chain Code Detection method need relate to definite problem of initial point, and this method is for noise effect straight-line detection poor effect is arranged in addition.
Summary of the invention
The invention provides a kind of gray level image cathetus and extract and extremity of segment point detecting method and system, to overcome existing method calculation of complex, easy affected by noise, the problem that can not detect straight line parameter and straight line end points simultaneously.
The invention provides a kind of method of extracting image cathetus and/or line segment end points, comprising:
Step 1 is carried out spherical projection with image;
Step 2 detects the circular arc on the sphere great circle;
Step 3 utilizes described circular arc to obtain straight-line equation and/or line segment end points.
In one example, also comprise step 5 before the step 1, extract edge of image; In the step 1, the point on the edge is carried out spherical projection.。
In one example, also comprise step 6 before the step 5, image is carried out filtering.
In one example, step 1 comprises:
Step 10, setting up with the true origin is that the centre of sphere, sphere diameter are 1 ball;
Step 11 with the projection model of true origin as projection centre, and makes the geometric center of intramarginal image and sphere tangent;
Step 12 projects to the point on the image on the sphere one to one.
In one example, step 2 comprises:
Step 20, the normal vector of detection sphere great circle;
Step 21 utilizes the normal vector of sphere great circle to separate point on the sphere great circle;
Step 22 utilizes point on the sphere great circle to obtain the end points of the circular arc on the sphere great circle.
In one example, in the step 21, the inner product between the point coordinate vector on the normal vector that utilizes the sphere great circle and the sphere is separated the point on the sphere great circle; If inner product is less than preset value, then the point on the sphere is the point on the sphere great circle.
In one example, in the step 22, utilize the extreme value of inner product between the intersecting point coordinate vector of the normal vector of sphere great circle and ball and the point coordinate vector on the sphere great circle to obtain the end points of the circular arc on the sphere great circle.
In one example, establish point coordinate Q:(q on the image
xq
y), the geometric center point T:(t of image
xt
y), then the coordinate of projection model mid point is
The point on the connection layout picture and the intersection point of projection centre and sphere are the projection of point on sphere on the image, and subpoint is designated as: P:(p
xp
yp
z) satisfy:
Then
The normal vector of sphere great circle and the intersection point of ball at the coordinate figure on x plane more than or equal to zero.
In one example, in the step 3:
If the normal vector V=(V of sphere great circle
xV
yV
Z), sphere great circle place plane equation is V
xX+V
yY+V
ZZ=0, plane of delineation equation are z=-1, and then straight-line equation is V
xX+V
yY=V
Z
If sphere orthodrome end points coordinate P:(p
xp
yp
z), then extremity of segment point coordinate is:
The invention provides a kind of system that extracts image cathetus and/or line segment end points, comprising:
Projection module is used for image is carried out spherical projection;
Module arc extraction module is used to extract the circular arc on the sphere great circle;
Computing module is used to utilize described circular arc to obtain straight-line equation and/or line segment end points.
In one example, also comprise the edge extracting module, be used to extract edge of image.
In one example, also comprise filtration module, be used for image is carried out filtering.
Technical scheme provided by the invention is simple, and antinoise power can be strong, and can detect straight line parameter and/or straight line end points simultaneously.
Description of drawings
Come the present invention is described in further detail below in conjunction with accompanying drawing, wherein:
Fig. 1 is that straight line provided by the invention extracts and extremity of segment point detecting method process flow diagram
Fig. 2 is the spherical projection illustraton of model;
Fig. 3 is a spherical arc end-point detection schematic diagram.
Embodiment
Method provided by the invention comprises as shown in Figure 1:
In order to realize spherical projection, at first to set up the projection sphere.Setting up with the true origin among the present invention is the centre of sphere, and sphere diameter is 1 ball.Sphere is designated as S, and the coordinate of putting on the sphere is: N:(n
xn
yn
z), have
Secondly, set up projection model, as shown in Figure 1, wherein C is a projection centre, and O is the centre of sphere, and C overlaps with O, and S is that the centre of sphere is the sphere of O, Q
PBe the point on the image, L is the line of picture point and projection centre C, and P is that the intersection point of L and sphere is Q
PSubpoint on sphere.Among the present invention, projection centre is got the centre of sphere (true origin), and the plane of delineation and sphere are tangent, and real image is a limited area, makes the geometric center of image-region and point of contact overlap.
At last, utilize projection model with man-to-man the projecting on the sphere of point on the plane of delineation.Pixel coordinate in the image-region, Q:(q
xq
y), geometric center point T:(t
xt
y), the coordinate of picture point is in the projection model:
The intersection point of point and projection centre and sphere is the projection of point on sphere on the image on the connection layout picture, and subpoint is designated as: P:(p
xp
yp
z) satisfy:
Particularly, set up the normal equation of constraint of sphere great circle, utilize Hough change detection great circle parameter, the parameter of great circle is the normal vector on plane, great circle place.The inner product of vectors of putting on the normal vector on plane, great circle place and the great circle is zero, chooses unit normal vector as parameter, and the point on the great circle is a variable.The plane at note sphere great circle place is π, and unit normal vector is: V=(v
xv
yv
z), the coordinate vector of putting on the great circle: P:(p
xp
yp
z), equation of constraint:
(v
x?v
y?v
z)·(p
x?p
y?p
z)=0。
Utilize the random Hough transformation on the sphere in parameter space, to ask extreme value to determine parameter.
A) two points of stochastic sampling on sphere are remembered 2 coordinate vector: P
iP
j, the cross product of compute vector, P
Ij=P
j* P
j, repeated sampling obtains the cross product vector space N time, and the cross product vector space is the great circle parameter space, if there be m the not orthodrome of coplanar on the sphere, then naming a person for a particular job with this m great circle parameter at parameter space is that the center becomes clustering distribution.
B) utilize the method for K rank average to calculate the cluster centre of big space of circles.The value at center is the great circle normal vector.Note: V
1V
2V
m
In order to detect end points, need to separate the point on the sphere great circle.After obtaining the normal vector on plane, sphere great circle place, separating the some employing inner product that belongs to this great circle on the sphere is zero equation.Because the influence of sum of errors image resolution ratio, inner product equation of constraint are zero inapplicable, need be adjusted into one near zero threshold value, be point on the great circle less than the point of threshold value.
Particularly, calculate the inner product of umbilical point and great circle parameter, the coordinate vector P that puts on the sphere
1P
2P
n, note
The C of great circle
jThe normal vector parameter is V
j, as shown in Figure 3:
If g
i≤ τ (threshold tau is less than 0.015) is P then
i∈ C
j
After isolating the point on the sphere great circle, detect sphere orthodrome end points.Particularly, great circle C
jBe designated as with the intersection point vector of sphere:
(intersection point has two, selects for use
), the point on the isolated great circle is designated as: P
1P
2P
k,
If:
P then
f, P
eEnd points for line segment.
Step 107, carry out straight line parameter and end points and calculate.The plane at great circle place and the intersection of the plane of delineation are the straight line in the image, set up projection model and coordinate system after, plane of delineation equation is fixed, plane, great circle place can obtain by a some French equation on the sphere.The equation on two planes goes the Z value just can get the equation of straight line.End points on the great circle is directly tried to achieve by the projective transformation transforming relationship.
Particularly, utilize the transformation relation of umbilical point and straight line to restore straight line in the original image.
Sphere great circle place planar process vector: V=(V
xV
yV
Z),
Sphere great circle place plane equation is: V
xX+V
yY+V
ZZ=0,
Plane of delineation equation is: z=-1,
Then the equation of straight line is: V
xX+V
yY=V
Z
Sphere orthodrome end points coordinate is: P:(p
xp
yp
z), then
The above only is a preferred implementation of the present invention, but protection domain of the present invention is not limited thereto.Any those skilled in the art all can carry out suitable change or variation to it in technical scope disclosed by the invention, and this change or variation all should be encompassed within protection scope of the present invention.
Claims (12)
1. a method of extracting image cathetus and/or line segment end points is characterized in that, comprising:
Step 1 is carried out spherical projection with image;
Step 2 is extracted the circular arc on the sphere great circle;
Step 3 utilizes described circular arc to obtain straight-line equation and/or line segment end points.
2. the method for claim 1 is characterized in that, also comprises step 5 before the step 1, extracts edge of image; In the step 1, the point on the edge is carried out spherical projection.
3. method as claimed in claim 2 is characterized in that, also comprises step 6 before the step 5, and image is carried out filtering.
4. method as claimed in claim 2 is characterized in that step 1 comprises:
Step 10, setting up with the true origin is that the centre of sphere, sphere diameter are 1 ball;
Step 11 with the projection model of true origin as projection centre, and makes the geometric center of intramarginal image and sphere tangent;
Step 12 projects to the point on the image on the sphere one to one.
5. method as claimed in claim 4 is characterized in that step 2 comprises:
Step 20, the normal vector of detection sphere great circle;
Step 21 utilizes the normal vector of sphere great circle to separate point on the sphere great circle;
Step 22 utilizes point on the sphere great circle to obtain the end points of the circular arc on the sphere great circle.
6. method as claimed in claim 5 is characterized in that, in the step 21, the inner product between the point coordinate vector on the normal vector that utilizes the sphere great circle and the sphere is separated the point on the sphere great circle; If inner product is less than preset value, then the point on the sphere is the point on the sphere great circle.
7. method as claimed in claim 5 is characterized in that, in the step 22, utilizes the extreme value of inner product between the intersecting point coordinate vector of the normal vector of sphere great circle and ball and the point coordinate vector on the sphere great circle to obtain the end points of the circular arc on the sphere great circle.
8. method as claimed in claim 7 is characterized in that, establishes the point coordinate Q:(q on the image
xq
y), the geometric center point T:(t of image
xt
y), then the coordinate of projection model mid point is
The point on the connection layout picture and the intersection point of projection centre and sphere are the projection of point on sphere on the image, and subpoint is designated as: P:(p
xp
yp
z) satisfy:
Then
The normal vector of sphere great circle and the intersection point of ball at the coordinate figure on x plane more than or equal to zero.
9. method as claimed in claim 8 is characterized in that, in the step 3:
If the normal vector V=(V of sphere great circle
xV
yV
Z), sphere great circle place plane equation is V
xX+V
yY+V
ZZ=0, plane of delineation equation are z=-1, and then straight-line equation is V
xX+V
yY=V
Z
10. a system that extracts image cathetus and/or line segment end points is characterized in that, comprising:
Projection module is used for image is carried out spherical projection;
Module arc extraction module is used to extract the circular arc on the sphere great circle;
Computing module is used to utilize described circular arc to obtain straight-line equation and/or line segment end points.
11. system as claimed in claim 10 is characterized in that, also comprises the edge extracting module, is used to extract edge of image.
12., it is characterized in that as claim 10 or 11 described systems, also comprise filtration module, be used for image is carried out filtering.
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CN106162277A (en) * | 2015-03-31 | 2016-11-23 | 乐视致新电子科技(天津)有限公司 | A kind of identification operates the method and apparatus of object, intelligent terminal |
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CN106296645A (en) * | 2015-06-25 | 2017-01-04 | 株式会社理光 | Image processing method and image processing apparatus |
CN107678444A (en) * | 2017-06-30 | 2018-02-09 | 中国航空无线电电子研究所 | A kind of method for realizing Parallel offset flight |
CN108520202A (en) * | 2018-03-15 | 2018-09-11 | 华南理工大学 | Confrontation robustness image characteristic extracting method based on variation spherical projection |
CN108520202B (en) * | 2018-03-15 | 2020-06-19 | 华南理工大学 | Method for extracting image characteristics with robustness resistance based on variational spherical projection |
CN114880980A (en) * | 2022-05-25 | 2022-08-09 | 上海合见工业软件集团有限公司 | Position data processing method for EDA tool, electronic device, and medium |
CN114880980B (en) * | 2022-05-25 | 2022-11-25 | 上海合见工业软件集团有限公司 | Position data processing method for EDA tool, electronic device and medium |
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