CN106228531A - Automatic vanishing point scaling method based on horizon search and system - Google Patents

Automatic vanishing point scaling method based on horizon search and system Download PDF

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CN106228531A
CN106228531A CN201610492617.9A CN201610492617A CN106228531A CN 106228531 A CN106228531 A CN 106228531A CN 201610492617 A CN201610492617 A CN 201610492617A CN 106228531 A CN106228531 A CN 106228531A
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horizon
vanishing point
top view
straight
line
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CN106228531B (en
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刘鹏
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Kai Yi (beijing) Technology Co Ltd
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G06V20/50—Context or environment of the image
    • G06V20/56—Context or environment of the image exterior to a vehicle by using sensors mounted on the vehicle
    • G06V20/588—Recognition of the road, e.g. of lane markings; Recognition of the vehicle driving pattern in relation to the road
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30248—Vehicle exterior or interior
    • G06T2207/30252—Vehicle exterior; Vicinity of vehicle
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30248—Vehicle exterior or interior
    • G06T2207/30252—Vehicle exterior; Vicinity of vehicle
    • G06T2207/30256—Lane; Road marking

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Abstract

The invention discloses automatic vanishing point scaling method based on horizon search and system, method includes: set up horizon situation template；According to horizontal line position, current position, generate the inverse perspective mapping matrix corresponding to described horizon；The top view that described horizon is corresponding is generated by described inverse perspective mapping matrix；Carry out straight-line detection in a top view, it is determined that this horizon is the most correct；If correct, then, by the straight line that detects in top view on inverse perspective mapping to perspective view, take these straight lines intersection point at perspective view as vanishing point；If incorrect, then base area horizontal line situation template, using next horizon as current position horizontal line, continues checking.The present invention utilizes the method for cyclic search, and search pressure is shared time dimension, and calculation resources consumes low.It addition, the present invention is without any priori conditions, can realize full automatic calibration vanishing point, the automatic vanishing point of realization truly is demarcated.

Description

Automatic vanishing point scaling method based on horizon search and system
Technical field
The present invention relates to image processing field, particularly to the automatic vanishing point scaling method searched for based on horizon and be System.
Background technology
The senior drive assist system (ADAS) of view-based access control model algorithm, vanishing point position is the key input of the most every technology Information, including leading vehicle distance calculating, pedestrian's range estimation, lane detection.The diversity installed due to photographic head, causes vanishing point Position in acquired image varies, and existing ADAS system is typically determined by artificial demarcation or automatic Calibration The position of vanishing point.Manually demarcate it is generally required to professional and technical personnel accurately installs, high cost, be not discussed.At automatic Calibration In the method for vanishing point, common method includes:
1. by full figure detection of straight lines or the method for lane line
This method is many by filtering image by the method for edge filter in artwork, then by Hough transformation detection of straight lines. In the straight line detected, find intersection two-by-two, in the intersection point of gained, filter out the point in heart region the most in the picture, and with surplus The mean location of remaining point is as vanishing point.
2. by G-sensor sensor and lane detection
This method is by G-sensor sensor, it is thus achieved that the photographic head angle of pitch, then estimates image according to image-forming principle Position, horizon.Then utilize lane detection module, take the intersection point of a plurality of lane line as vanishing point.
3. by Foregut fermenters and lane detection
There is a following relation proportionate relationship of front height and photographic head height and position, horizon:
h o h t = v t - v b v o - v b
Wherein h0Represent front truck true altitude, hcRepresent photographic head true altitude, vtFor front truck top vertical seat in the picture Mark, vbFor front truck bottom vertical coordinate in the picture, voHorizon vertical coordinate.
Counter pushing away can obtain:
v 0 = h c ( v t - v b ) h o + v b
Owing to car height domain of walker is the least, h0Being approximately 1.5m, remaining variables is also known.Thus can be evaluated whether Go out horizontal position.Then on the premise of position, known horizon, utilize lane detection module, take a plurality of lane line Intersection point is as vanishing point.
There is following defect in said method:
In method 1, in the case of horizontal line indefinitely, carrying out straight-line detection in the range of full figure needs to consume in a large number Calculating resource, and have many interference straight line (such as road surface word, roadside railing etc.) not converge at vanishing point, can be to result Impact.
In method 2, depending on hardware, the hardware technique of G-sensor can directly affect horizontal estimation result, carefully Micro-deviation may result in vanishing point and is out of one's reckoning, and process is uncontrollable.
In method 3, depend on Foregut fermenters module, in the case of front is inaccurate without vehicle or vehicle detection, Horizon can be caused to be out of one's reckoning, thus affect the calibration result of vanishing point.
Summary of the invention
The technical problem to be solved in the present invention is, does not relies on the hardware of Foregut fermenters and G-sensor, automatically goes out Point is demarcated.
Solve above-mentioned technical problem, the invention provides a kind of automatic vanishing point scaling method based on horizon search, bag Include:
Set up horizon situation template；
According to horizontal line position, current position, generate the inverse perspective mapping matrix corresponding to described horizon；
The top view that described horizon is corresponding is generated by described inverse perspective mapping matrix；
Carry out straight-line detection in a top view, it is determined that this horizon is the most correct；
If correct, then, by the straight line that detects in top view on inverse perspective mapping to perspective view, take these straight lines and exist The intersection point of perspective view is as vanishing point；
If incorrect, then base area horizontal line situation template, using next horizon as current position horizontal line, continues checking.
Further, choose 11 alternatively horizontal line positions, set up horizontal line situation template as follows:
{y0、y1、y2、y3、y4、y5、y6、y7、y8、y9、y10, 11 that choose image central region are separated by uniform horizontal line.
Further, the method generating inverse perspective mapping matrix corresponding to described horizon is as follows:
Calculate inverse perspective mapping matrix T-1With horizon center point P0Function；
Tn -1=f-1(yn)
Wherein, P0Vertical coordinate be horizon coordinate yn, abscissa be fixed value be the half of fluoroscopy images width.
Further, carry out straight-line detection result in a top view to be represented by the two of straight line end points:
Straight line the L=((x detectedP,yp),(xQ,yQ)),
Wherein, (xP,yp), (xQ,yQ) it is respectively upper extreme point P and the coordinate of lower extreme point Q, the seat of upper and lower two end points of straight line Mark can represent line correspondence.
Further, straight-line detection is carried out in a top view, it is determined that when this horizon is the most correct,
If any two straight lines meet during following condition parallel with the angle of x-axis, i.e. on top view, the straight line detected Angle with x-axis
|α1-α2|≤ε
ε is the threshold value judging the most parallel minimum angles difference of two straight lines.
Further, wherein ε=5 °.
Further, wherein angle with x-axis can be tried to achieve by the extreme coordinates of straight line:
α = a r c t a n ( x Q - x P y Q - y P )
Wherein, xP,ypAnd xQ,yQIt is respectively upper extreme point P and the coordinate of lower extreme point Q.
Further, it is determined that this horizon the most correctly includes following condition:
If having at least 3 frame horizon to meet parallel condition in continuous 10 frames, then it is assumed that horizon is correct.
Present invention also offers a kind of automatic vanishing point calibration system based on horizon search, including:
Modular unit, sets up horizon situation template；
Top view signal generating unit, according to horizontal line position, current position, generates the inverse perspective mapping matrix corresponding to described horizon； The top view that described horizon is corresponding is generated by described inverse perspective mapping matrix；
Straight-line detection unit, in order to carry out straight-line detection in a top view；
Checking parallel lines unit, the most correct in order to judge this horizon；If correct, then straight by what top view detected Line, on inverse perspective mapping to perspective view, takes these straight lines intersection point at perspective view as vanishing point；If incorrect, then base area Horizontal line situation template, using next horizon as current position horizontal line, continues checking.
Further, also include search unit, in order to verify parallel lines unit judge that this horizon is incorrect time, according to Horizon situation template, using next horizon as current position horizontal line, continues checking.Until being verified.If institute There is horizon the most not verified, the most again start repeated authentication from first horizon.
Beneficial effects of the present invention:
1) the automatic vanishing point scaling method that the present invention searches for based on horizon, carries out straight-line detection in a top view, it is determined that This horizon is the most correct；If correct, then, by the horizon in top view in perspective transform to perspective view, take those Horizons Line intersection point in the perspective is as vanishing point；If incorrect, then continue search for the Horizon of next frame according to horizon situation template Line position.The present invention utilizes the method for cyclic search, and search pressure is shared time dimension, and calculation resources consumes low.
2) present invention is without any priori conditions, can realize full automatic calibration vanishing point, by setting up position, horizon mould Plate；According to the current position horizontal line coordinate that detects in the situation template of described horizon, generate corresponding to described horizon is inverse Perspective transformation matrix；The top view that described horizon is corresponding is generated by described inverse perspective mapping matrix；Carry out in a top view Straight-line detection, it is determined that this horizon is the most correct.
3) vanishing point in the present invention refers to, dead ahead pole, visual field point at a distance, i.e. horizon and the friendship of sight line dead ahead Point, vanishing point be in the visual field before and after the convergent point of straight line (lane line) that extends.Senior driving auxiliary at view-based access control model algorithm is In system (ADAS), vanishing point position is the key input information of the most every technology, includes but not limited to leading vehicle distance calculating, pedestrian Range estimation, lane detection.So having the biggest value and effect for ADAS.
Accompanying drawing explanation
Fig. 1 is the schematic flow sheet of the automatic vanishing point scaling method that the present invention searches for based on horizon.
Fig. 2 is to set up horizon situation template simulation schematic diagram in Fig. 1.
Fig. 3 (a) Fig. 3 (c) is the top view schematic diagram generated in Fig. 1.
Fig. 4 is to verify in Fig. 1 that whether horizon is the schematic diagram of parallel lines.
Fig. 5 is the vanishing point method for searching schematic diagram in Fig. 1.
Fig. 6 is the structural representation of the automatic vanishing point calibration system that the present invention searches for based on horizon.
Detailed description of the invention
For making the object, technical solutions and advantages of the present invention clearer, below in conjunction with specific embodiment, and reference Accompanying drawing, the present invention is described in more detail.
Fig. 1 is the schematic flow sheet of the automatic vanishing point scaling method that the present invention searches for based on horizon.
Step S100 sets up horizon situation template；
Step S101, according to horizontal line position, current position, generates the inverse perspective mapping matrix corresponding to described horizon；
Step S102 generates, by described inverse perspective mapping matrix, the top view that described horizon is corresponding；
Step S103 carries out straight-line detection in a top view,
Step S104 judges that this horizon is the most correct；
If step S105 is correct, then, by the straight line that detects in top view on inverse perspective mapping to perspective view, take this A little straight lines at the intersection point of perspective view as vanishing point；
If step S106 is incorrect, then base area horizontal line situation template, using next horizon as current position horizontal line, continues Continuous checking.
Automatic vanishing point scaling method in the present embodiment, it is not necessary to any priori conditions, can realize full automatic calibration vanishing point, By setting up horizon situation template；According to the current position horizontal line coordinate detected in the situation template of described horizon, generate Inverse perspective mapping matrix corresponding to described horizon；Corresponding the bowing in described horizon is generated by described inverse perspective mapping matrix View；Carry out straight-line detection in a top view, it is determined that this horizon is the most correct.
Preferred as in the present embodiment, chooses 11 alternatively horizontal line positions in described step S100, sets up as follows Horizon situation template:
{y0、y1、y2、y3、y4、y5、y6、y7、y8、y9、y10}。
Preferred as in the present embodiment, in described step S100 step S101 generate corresponding to described horizon inverse The method of perspective transformation matrix is as follows:
Calculate inverse perspective mapping matrix T-1With horizon center point P0Function；
Tn -1=f-1(yn)
Wherein, P0Vertical coordinate be horizon coordinate yn, abscissa be fixed value be the half of fluoroscopy images width.
Preferred as in the present embodiment, carries out straight-line detection result the most in a top view by straight line Two end points represent:
Straight line the L=((x detectedP,yp),(xQ,yQ)),
Wherein, (xP,yp), (xQ,yQ) it is respectively upper extreme point P and the coordinate of lower extreme point Q.
Preferred as in the present embodiment, carries out straight-line detection, it is determined that this horizon in step S104 in a top view Time the most correct,
If any two straight lines meet during following condition parallel with the angle of x-axis,
|α1-α2|≤ε
ε is the threshold value judging the most parallel minimum angles difference of two straight lines, wherein ε=5 °.
Preferred as in the present embodiment, wherein the angle with x-axis can be tried to achieve by the extreme coordinates of straight line:
α = a r c t a n ( x Q - x P y Q - y P )
Wherein, xP,ypAnd xQ,yQIt is respectively upper extreme point P and the coordinate of lower extreme point Q.
Preferred as in the present embodiment, judges in step S105 that this horizon the most correctly includes following condition:
If having at least 3 frame horizon to meet parallel condition in continuous 10 frames, then it is assumed that horizon is correct.
Inventive principle:
First, utilize the functional relationship of top view inverse perspective mapping and horizon coordinate, generate corresponding to the horizontal line of current position Inverse perspective mapping matrix T-1.In continuous 10 two field pictures afterwards, use this T-1Generate top view, and carry out straight-line detection.If 10 Have more than the straight line that 3 frames detect in frame and present parallel relation, then exit search.If exit criteria cannot be met, then change ground Horizontal line, repeat the above steps continues checking, until exiting search.After searching for successfully, the parallel lines in top view is entered Row perspective transform, takes its intersection point in the perspective as vanishing point.
Specifically, the concept of search is incorporated in vanishing point demarcation by the present invention, position, cyclic search horizon.
As in figure 2 it is shown, be that Fig. 1 sets up horizon situation template simulation schematic diagram.In figure, the line of labelling covers the biggest Position in the picture, horizon under part photographic head installation situation.Vertical coordinate corresponding to every horizon is designated as yn.From y0Open Begin, each horizon is carried out the checking of continuous 10 frames, if not met exit criteria, then jump to next horizon and continue Checking.If searching y10The most do not exit search, then continue from y0Restart.
Owing to, in actual application scenarios, the image that photographic head catches is in real-time change, the information that each two field picture comprises Amount is different from.Further, the demarcation of vanishing point is not required at once completing, it is only necessary to complete the most as precisely as possible Demarcate.So, the present invention does not travel through all of search target at same two field picture, but have employed the side of cyclic search Method, has shared search pressure time dimension, every 10 one horizon of frame checking, will not produce a large amount of computing in a frame.
1). top view generates
The first step of horizon proof procedure is to generate top view, and top view is by the lane line region of Visual Angle in Perspective image Be converted to overlook visual angle by inverse perspective mapping.
Calculate inverse perspective mapping matrix T-1Method the most highly developed, just have in OPENCV correspondence function, at this No longer introduce ins and outs.The method that base area horizontal line central point calculates inverse perspective mapping matrix is the most highly developed, and the present invention is not Reinflated introduction.
The most only need to know T-1Being the function of horizon center point P 0, the vertical coordinate of P0 is horizon coordinate yn, abscissa For the half of fluoroscopy images width, it it is fixed value.So, Tn -1Only relevant to yn.
Tn -1=f-1(yn)
Fig. 3 (a) Fig. 3 (c) is the top view schematic diagram generated in Fig. 1, and wherein Fig. 3 (a) Fig. 3 (c) is y4 respectively, The top view that y5, y6 horizon is corresponding.
2). straight-line detection
Carry out straight-line detection in a top view, owing to the size of top view is more much smaller than artwork, so the speed of straight-line detection Degree is quickly.The method of straight-line detection is very universal, such as Hough transformation and the method for enhancing projection, technology is the most no longer described in detail in detail thin Joint.
The straight line L detected, with upper extreme point P and the coordinate representation of lower extreme point Q:
L=((xP,yP),(xQ,yQ))
3). checking parallel lines
From top view above, if current position horizontal line is correct, then converge at vanishing point (example in Visual Angle in Perspective Such as lane line) straight line overlook in visual angle in parallel.Utilize this priori, it is possible to determine that horizon is the most just Really.
As shown in Figure 4, it is that Fig. 1 verifying, whether horizon is the schematic diagram of parallel lines, if any two straight lines and x-axis Angle meets following condition, the most parallel.
|α1-α2|≤ε
Through great many of experiments, ε=5 °.
The angle of straight line and x-axis can be tried to achieve by the extreme coordinates of straight line:
α = a r c t a n ( x Q - x P y Q - y P )
If having more than 3 frames or 3 frames to meet parallel condition in continuous 10 frames, then it is assumed that horizon is correct, exits search Flow process.
Finally, by the parallel lines in top view in perspective transform to perspective view.Perspective transform is inverse perspective mapping Inverse transformation, in OPENCV, have respective function, be not described in detail in this.
Being the vanishing point method for searching schematic diagram in Fig. 1 as shown in Figure 5, the inverse transformation making inverse perspective mapping obtains perspective change Change:
(P'x,y,Q'x,y)=f (Px,y,Qx,y)
Taking those horizon intersection point in the perspective as vanishing point, the computational methods of vanishing point coordinate can be according to following public Formula:
x v p o int = ( y Q 2 , - y Q 1 , ) × x P 1 , × x P 2 , + ( y P 2 , - y P 1 , ) × x Q 1 , × x Q 2 , + ( y P 1 , - y Q 2 , ) × x P 2 , × x Q 1 , + ( y Q 1 , - y P 2 , ) × x P 1 , × x Q 2 , ( y P 1 , - y Q 1 , ) × ( x P 2 , - x Q 2 , ) + ( x P 1 , - x Q 1 , ) × ( y Q 2 , - y P 2 , )
y v p o int = ( x Q 2 , - x Q 1 , ) × y P 1 , × y P 2 , + ( x P 2 , - x P 1 , ) × y Q 1 , × y Q 2 , + ( x P 1 , - x Q 2 , ) × y P 2 , × y Q 1 , + ( x Q 1 , - x P 2 , ) × y P 1 , × y Q 2 , ( x P 1 , - x Q 1 , ) × ( y P 2 , - y Q 2 , ) + ( y P 1 , - y Q 1 , ) × ( x Q 2 , - x P 2 , )
It is the structural representation of the automatic vanishing point calibration system that the present invention searches for based on horizon as shown in Figure 6.
Automatic vanishing point calibration system 10 based on horizon search in the present embodiment, including:
Modular unit 1, sets up horizon situation template；
Top view signal generating unit 2, according to horizontal line position, current position, generates the inverse perspective mapping square corresponding to described horizon Battle array；The top view that described horizon is corresponding is generated by described inverse perspective mapping matrix；
Straight-line detection unit 3, in order to carry out straight-line detection in a top view；
Checking parallel lines unit 4, the most correct in order to judge this horizon；If correct, then will top view detect Straight line, on inverse perspective mapping to perspective view, takes these straight lines intersection point at perspective view as vanishing point；If incorrect, then basis Horizon situation template, using next horizon as current position horizontal line, continues checking.
Preferred as the present embodiment, automatic vanishing point calibration system 10 also includes search unit 5, in order at checking parallel lines Unit judges when this horizon is incorrect, base area horizontal line situation template, using next horizon as current position horizontal line, continues Checking.Until being verified.If all horizon are the most not verified, the most again start from first horizon to repeat Checking.
Automatic vanishing point calibration system in the present embodiment, the method utilizing cyclic search in search unit 5, search is pressed Power shares time dimension, and calculation resources consumes low.
Those of ordinary skill in the field it is understood that more than, described be only the present invention specific embodiment, and Be not used in the restriction present invention, all within the spirit and principles in the present invention, any modification, equivalent substitution and improvement etc. done, all Within protection scope of the present invention should being included in.

Claims (10)

1. an automatic vanishing point scaling method based on horizon search, it is characterised in that including:
Set up horizon situation template；
According to horizontal line position, current position, generate the inverse perspective mapping matrix corresponding to described horizon；
The top view that described horizon is corresponding is generated by described inverse perspective mapping matrix；
Carry out straight-line detection in a top view, it is determined that this horizon is the most correct；
If correct, then, by the straight line that detects in top view on inverse perspective mapping to perspective view, take these straight lines in perspective The intersection point of figure is as vanishing point；
If incorrect, then base area horizontal line situation template, using next horizon as current position horizontal line, continues checking.
Automatic vanishing point scaling method the most according to claim 1, it is characterised in that choose 11 alternatively horizontal line positions, Set up horizontal line situation template as follows:
{y0、y1、y2、y3、y4、y5、y6、y7、y8、y9、y10}。
Automatic vanishing point scaling method the most according to claim 1, it is characterised in that generate corresponding to described horizon is inverse The method of perspective transformation matrix is as follows:
Calculate inverse perspective mapping matrix T-1With horizon center point P0Function；
Tn -1=f-1(yn)
Wherein, P0Vertical coordinate be horizon coordinate yn, abscissa be fixed value be the half of fluoroscopy images width.
Automatic vanishing point scaling method the most according to claim 1, it is characterised in that carry out straight-line detection knot in a top view Fruit is represented by the two of straight line end points:
Straight line the L=((x detectedP,yp),(xQ,yQ)),
Wherein, (xP,yp), (xQ,yQ) it is respectively upper extreme point P and the coordinate of lower extreme point Q.
Automatic vanishing point scaling method the most according to claim 1, it is characterised in that carry out straight-line detection in a top view, Judge when this horizon is the most correct,
If any two straight lines meet during following condition parallel with the angle of x-axis,
|α1-α2|≤ε
ε is the threshold value judging the most parallel minimum angles difference of two straight lines.
Automatic vanishing point scaling method the most according to claim 5, it is characterised in that wherein ε=5 °.
7. the automatic vanishing point scaling method stated according to claim 5, it is characterised in that wherein the angle with x-axis can pass through straight line Extreme coordinates try to achieve:
α = a r c t a n ( x Q - x P y Q - y P )
Wherein, xP, ypAnd xQ, yQIt is respectively upper extreme point P and the coordinate of lower extreme point Q.
Automatic vanishing point scaling method the most according to claim 1, it is characterised in that judge that this horizon the most correctly includes Following condition:
If having at least 3 frame horizon to meet parallel condition in continuous 10 frames, then it is assumed that horizon is correct.
9. an automatic vanishing point calibration system based on horizon search, it is characterised in that including:
Modular unit, sets up horizon situation template；
Top view signal generating unit, according to horizontal line position, current position, generates the inverse perspective mapping matrix corresponding to described horizon；Pass through Described inverse perspective mapping matrix generates the top view that described horizon is corresponding；
Straight-line detection unit, in order to carry out straight-line detection in a top view；
Checking parallel lines unit, the most correct in order to judge this horizon；If correct, then the straight line warp that will detect in top view Cross inverse perspective mapping to perspective view, take these straight lines intersection point at perspective view as vanishing point；If incorrect, then base area horizontal line Situation template, using next horizon as current position horizontal line, continues checking.
10. according to the calibration system described in 9 claim 1, it is characterised in that also include search unit, in order to parallel in checking Line unit judges when this horizon is incorrect, base area horizontal line situation template, using next horizon as current position horizontal line, continues Continuous checking.Until being verified.If all horizon are the most not verified, the most again start weight from first horizon Review card.
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CN107316331B (en) * 2017-08-02 2020-04-14 浙江工商大学 Vanishing point automatic calibration method for road image
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CN111174796A (en) * 2019-12-31 2020-05-19 驭势科技(南京)有限公司 Navigation method based on single vanishing point, electronic equipment and storage medium
CN111210411A (en) * 2019-12-31 2020-05-29 驭势科技(南京)有限公司 Detection method of vanishing points in image, detection model training method and electronic equipment
CN111174796B (en) * 2019-12-31 2022-04-29 驭势科技（浙江）有限公司 Navigation method based on single vanishing point, electronic equipment and storage medium
CN111210411B (en) * 2019-12-31 2024-04-05 驭势科技（浙江）有限公司 Method for detecting vanishing points in image, method for training detection model and electronic equipment
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