CN105488485A - Lane line automatic extraction method based on vehicle trajectory - Google Patents
Lane line automatic extraction method based on vehicle trajectory Download PDFInfo
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- G—PHYSICS
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- 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
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Abstract
The invention discloses a lane line automatic extraction method based on a vehicle trajectory. The method comprises the following steps: step 1, extracting the vehicle trajectory; step 2, creating a vehicle trajectory image; step 3, eliminating trajectory adhesion between different lanes based on morphological close operation and erosion; and step 4, extracting a lane line by a minimum enclosing rectangle method. The lane line automatic extraction method based on the vehicle trajectory provided by the invention does not depend on a road marking, therefore, the lane line automatic extraction method is also applicable to road areas without markings or the markings are fuzzy; the invention can extract the lane lines of multiple lanes simultaneously and the efficiency is high; besides, an unmanned aerial vehicle has an advantage of being mobile, therefore, the unmanned aerial vehicle can be used for performing lane line extraction on road sections without traffic monitoring equipment.
Description
Technical field
The invention belongs to technical field of image processing, relate to a kind of method automatically extracting lane line based on track of vehicle, the present invention is intended to introduce a kind of blanket lane line extracting method, pavement marker is not existed or lane line under ambiguity to extract problem all applicable.
Background technology
Lane line builds the important composition composition of road conditions, and extracting lane line the traffic surveillance and control system of robotization is important function.Lane line extracts traffic study, as driving behavior detect, the method for the road network of classification (change, deviation etc.) and bicycle road level necessity of extracting that to be important be also.
At present, the lane line extracting method based on video is that such mode has some deficiency: 1) do not exist or fuzzy section roadmarking, cannot extract lane line by identifying that roadmarking completes lane line and extracts; 2) because the viewing angle problem of camera causes the lane line of extraction to have comparatively big error at far-end; 3) for the region not having monitoring camera, lane line cannot be realized and extract.Another kind of Lane detection method is based on GPS locator data, its principle carries GPS positioning equipment to cruise along road-center, then extract lane line based on gps data, the weak point of the method is that the positioning error of gps data is comparatively large, and therefore Precision in Roadway Recognition is low.
Summary of the invention
For the deficiency of existing lane line extracting method, the present invention proposes the lane line extracting method based on track of vehicle, adopt track of vehicle reverse push guide-car diatom.The present invention is the lane line extracting method based on track of vehicle, first to take photo by plane video extraction track of vehicle based on unmanned plane low latitude, then track of vehicle image is built based on track of vehicle, the track adhesion of changing between different tracks that track of vehicle causes is removed in applied morphology closed operation, caustic solution, then the minimum enclosed rectangle of track of vehicle on every bar track is calculated, the center line of this minimum enclosed rectangle is the center line in track, namely achieves lane line and extracts.
Lane line extraction method of the present invention, to take photo by plane video extraction track of vehicle based on unmanned plane, then based on vehicle operating track reverse push guide-car diatom, do not rely on road conditions (with or without pavement marker or whether fuzzy), there is general applicability.
The present invention enters a little with brand-new research, for lane line propose a kind of can the blanket lane line extraction method based on track of vehicle, realized by following step:
Step 1: track of vehicle extracts;
Based on the low latitude Aerial Images of unmanned plane, carry out track of vehicle extraction, extract result for obtaining best lane line, the track of vehicle number that every bar track is extracted is no less than 20, and namely this track needs at least 20 cars to pass through.Track extraction method can be manual extraction, also can based on existing automatic orbit extracting method such as particle filter, KLT feature point tracking or TLD, for building track of vehicle image in next step.
Step 2: track of vehicle image creation;
Create trace image with the track of vehicle extracted based on unmanned plane Aerial Images in step, track of vehicle raw data is discrete point, needs track of vehicle point to connect into curve according to the sequencing extracted here in the process creating track.The image creation of trace image divides following three steps: the blank image 1) creating white background, and the Aerial Images of image size and extraction track etc. are large; 2) by track of vehicle Drawing of Curve to blank image.Because track of vehicle is vector, there is not width problem, but track drafting considers this live width factor to the process need of image, the live width of track of vehicle gives tacit consent to 1/6 of a transverse width of picking up the car here, and lateral direction of car width needs hand dipping to obtain;
Step 3: eliminate track adhesion between different track from corrosion based on closing operation of mathematical morphology;
The track of many cars, after coincidence, can form coincidence district, but can there is gap between track, adopts closing operation of mathematical morphology method to fill track space, to form complete connected region here.Vehicle lane-changing can cause track adhesion between different track in trace image, affect the accuracy that follow-up lane line extracts, therefore need to eliminate this adhesion, here morphological erosion method is adopted to process trace image, to eliminate track adhesion, wherein corrosion structure element adopts round, and radius of a circle is 1/5 of vehicle width.After Image erosion, have track fragment and exist, here by length characteristic, track fragment length being less than image level width 1/2 screens out.
Step 4: Minimum Enclosing Rectangle method extracts lane line
To the trace image having interrupted track adhesion in upper step, first calculate the minimum enclosed rectangle of track of vehicle on every bar track, then calculate the center line of minimum enclosed rectangle, namely obtain the lane line of road.
The invention has the advantages that:
(1) the present invention utilizes vehicle generally along the characteristic that track center line travels, and reverse push guide-car diatom, has method innovation;
(2) unmanned plane has moveable advantage, therefore can be used for carrying out lane line extraction to the section without traffic monitoring apparatus;
(3) the present invention extracts lane line and does not rely on roadmarking, therefore to without graticule or the fuzzy road area of graticule applicable equally;
(4) the present invention can extract the lane line of multilane simultaneously, and efficiency is high.
Accompanying drawing explanation
Fig. 1 is the track of vehicle stacking diagram of video extraction of taking photo by plane based on unmanned plane;
Fig. 2 is the trace image (bianry image) built based on track of vehicle;
Fig. 3 eliminates track adhesion figure between different track based on closing operation of mathematical morphology, corrosion;
Fig. 4 is for screen out track fragment based on track connected region length;
Fig. 5 is the minimum enclosed rectangle figure calculating track connected region;
Fig. 6 is the center line chart calculating minimum enclosed rectangle;
Fig. 7 is the lane line (Four-Lane Road) extracted;
Fig. 8 is method flow diagram of the present invention.
Embodiment
Below in conjunction with drawings and Examples, the present invention is described in further detail.
The invention provides a kind of lane line extracting method based on track of vehicle, track of vehicle used is based on video extraction of taking photo by plane.The present invention is the lane line extracting method based on track of vehicle, first to take photo by plane video extraction track of vehicle based on the low latitude of unmanned plane, then builds track of vehicle image based on track of vehicle; The track adhesion of changing between different tracks that track of vehicle causes is removed in applied morphology closed operation, caustic solution; Based on track regions length characteristic, screen out non-vehicle track regions; Then calculate the minimum enclosed rectangle of every bar track track, the center line of this minimum enclosed rectangle is the center line in track, namely achieves lane line and extracts.The above-mentioned lane line extracting method based on track of vehicle, as shown in Figure 8, concrete treatment step is as follows for flow process:
Step 1: track of vehicle extracts;
Based on the low latitude Aerial Images of unmanned plane, extract track of vehicle.Track extraction method can be manual extraction, also can based on existing automatic orbit extracting method such as particle filter, KLT feature point tracking or TLD, for building track of vehicle image in next step.Extract result for obtaining best lane line, the track of vehicle number that every bar track is extracted should be no less than 20, and namely every bar track needs at least 20 cars to pass through.The track of vehicle overlap of extraction is plotted on Aerial Images, Figure 1 shows that the Overlay figure of track of vehicle.
Step 2: track of vehicle picture construction;
Create trace image with the track of vehicle extracted based on unmanned plane Aerial Images in step, track of vehicle raw data is discrete point, needs track of vehicle point to connect into curve according to the sequencing extracted here in the process creating track.The image creation of trace image divides following three steps: the blank image 1) creating white background, and the Aerial Images of image size and extraction track etc. are large; 2) by track of vehicle Drawing of Curve to blank image.Because track of vehicle is vector, there is not width problem, but track drafting considers this live width factor to the process need of image, the live width of track of vehicle gives tacit consent to 1/6 of a transverse width of picking up the car here, and lateral direction of car width needs hand dipping to obtain.Figure 2 shows that the trace image of establishment, this figure is bianry image;
Step 3: eliminate track adhesion between different track from corrosion based on closing operation of mathematical morphology;
The track of many cars, after coincidence, can form coincidence district, but can there is gap between track, adopts closing operation of mathematical morphology method to fill track space, to form complete connected region here.Vehicle lane-changing can cause the track of vehicle adhesion in trace image between different track, as shown in Figure 2, article four, between track, there is the adhesion phenomenon of track, this can affect the accuracy that follow-up lane line extracts, therefore need to eliminate this adhesion, adopt morphological erosion method to process trace image, to eliminate track adhesion here, wherein corrosion structure element adopts circle, and radius of a circle is 1/5 of vehicle width.In trajectory diagram shown in Fig. 3, the track of Tu2Zhong Huan road vehicle is screened out, and namely eliminates track adhesion part.As shown in Fig. 3 lower right corner, the non-track regions of part is not eliminated, and needs to screen out, here based on the length characteristic of track of vehicle, track connected region length being less than image length 1/2 screens out, and in Fig. 4, display has screened out the shorter non-vehicle path portion in the lower right corner in Fig. 3.
Step 4: Minimum Enclosing Rectangle method extracts lane line
To the trace image having interrupted track adhesion in step 3, calculate the minimum enclosed rectangle of track of vehicle on every bar track, track of vehicle as shown in Figure 5 on each track is by a long rectangle outsourcing, then the center line of minimum enclosed rectangle is calculated, as shown in Figure 6, this center line is the lane line of road, namely achieves lane line and extracts, as shown in Figure 7, the lane line in four tracks is extracted in display.
Claims (4)
1., based on the lane line extraction method of track of vehicle, comprise following step:
Step 1: track of vehicle extracts;
Based on the low latitude Aerial Images of unmanned plane, carry out track of vehicle extraction;
Step 2: track of vehicle image creation;
Create and the equal-sized blank image of Aerial Images, track of vehicle raw data is discrete point, and the discrete point of track of vehicle is plotted to blank image according to the sequencing extracted, and discrete point connects into curve, form track of vehicle image, the live width of track of vehicle is set;
Step 3: eliminate track adhesion between different track based on morphological dilations corrosion;
After the track coincidence of many cars, form coincidence district, between track, there is gap, adopt closing operation of mathematical morphology to fill track space, form complete connected region; Vehicle lane-changing causes track adhesion between different track in trace image, adopts morphological erosion method to process trace image, eliminates track adhesion;
Step 4: Minimum Enclosing Rectangle method extracts lane line;
To the trace image obtained in step 3, obtain the minimum enclosed rectangle of track of vehicle on every bar track, calculate the center line of minimum enclosed rectangle, center line is the lane line of road.
2. the lane line extraction method based on track of vehicle according to claim 1, in described step 1, the track of vehicle number that every bar track is extracted is no less than 20.
3. the lane line extraction method based on track of vehicle according to claim 1, in described step 2, the live width of track of vehicle is 1/6 of lateral direction of car width.
4. the lane line extraction method based on track of vehicle according to claim 1, in described step 3, in morphological erosion method, corrosion structure element adopts round, and radius of a circle is 1/5 of vehicle width; After Image erosion, track connected region length being less than image length 1/2 screens out.
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| CN109284674A (en) * | 2018-08-09 | 2019-01-29 | 浙江大华技术股份有限公司 | A kind of method and device of determining lane line |
| CN109785667A (en) * | 2019-03-11 | 2019-05-21 | 百度在线网络技术（北京）有限公司 | Deviation recognition methods, device, equipment and storage medium |
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| CN114906152A (en) * | 2022-04-22 | 2022-08-16 | 合众新能源汽车有限公司 | Lane line construction method, lane line construction device, electronic device, and computer-readable storage medium |
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| CN109284674A (en) * | 2018-08-09 | 2019-01-29 | 浙江大华技术股份有限公司 | A kind of method and device of determining lane line |
| CN109284674B (en) * | 2018-08-09 | 2020-12-08 | 浙江大华技术股份有限公司 | Method and device for determining lane line |
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| CN109785667A (en) * | 2019-03-11 | 2019-05-21 | 百度在线网络技术（北京）有限公司 | Deviation recognition methods, device, equipment and storage medium |
| CN110906940A (en) * | 2019-10-26 | 2020-03-24 | 武汉中海庭数据技术有限公司 | Lane sideline aggregation method based on track direction |
| CN110942038A (en) * | 2019-11-29 | 2020-03-31 | 腾讯科技（深圳）有限公司 | Traffic scene recognition method, device, medium and electronic equipment based on vision |
| CN111551958A (en) * | 2020-04-28 | 2020-08-18 | 北京踏歌智行科技有限公司 | Mining area unmanned high-precision map manufacturing method |
| CN111551958B (en) * | 2020-04-28 | 2022-04-01 | 北京踏歌智行科技有限公司 | Mining area unmanned high-precision map manufacturing method |
| CN111738207A (en) * | 2020-07-13 | 2020-10-02 | 腾讯科技（深圳）有限公司 | Lane line detection method and device, electronic device and readable storage medium |
| CN112092815A (en) * | 2020-09-02 | 2020-12-18 | 北京航空航天大学 | Vehicle track changing tracking control method based on model prediction |
| CN114906152A (en) * | 2022-04-22 | 2022-08-16 | 合众新能源汽车有限公司 | Lane line construction method, lane line construction device, electronic device, and computer-readable storage medium |
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