CN104318761A - Highway-scene-based detection and vehicle detection tracking optimization method - Google Patents
Highway-scene-based detection and vehicle detection tracking optimization method Download PDFInfo
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- CN104318761A CN104318761A CN201410436667.6A CN201410436667A CN104318761A CN 104318761 A CN104318761 A CN 104318761A CN 201410436667 A CN201410436667 A CN 201410436667A CN 104318761 A CN104318761 A CN 104318761A
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Abstract
The invention discloses a highway-scene-based detection and vehicle detection tracking optimization method. The method comprises the following steps: step one, detecting a lane line in a video and marking and recording the lane line information; step two, detecting vehicles in the marked lane line and marking and recording vehicle information; step three, detecting a distance between vehicles in the video and marking and recording the vehicle distance; step four, determining whether the vehicle distance is larger than a given threshold value; if so, entering the step five; and if not, returning to the step one; step five, recording a vehicle distance Di within time t, marking the maximum value and the minimum value, and determining whether the maximum and minimum value difference is less than a given value; if so, entering the step six; if not, returning to the step one; step six, determining scene switching to the highway; and step seven, tracking the marked vehicle. The method has the following advantages: the number of processed frames of the video can be reduced; the calculated amount is reduced; and the real-time performance is improved.
Description
Technical field
The present invention relates to a kind of mechanical vision inspection technology, a kind of method of particularly detection based on highway scene and automobile detecting following optimization.
Background technology
Along with the development of society, the living standard of people's life improves constantly, and automobile is gradually gained popularity.But the thing followed is traffic hazard, and especially pernicious traffic hazard trend constantly rises.Especially on a highway, due to features such as its traffic volume are large, the speed of a motor vehicle is fast, once there is traffic hazard, its huge vehicle flowrate very easily forms tens the even chain traffic hazard of up to a hundred car collisions, the loss caused is also just inestimable, is all often that loss is serious, car crash.For reducing the incidence of traffic hazard, researchist has proposed the concept of intelligent vehicle.
In order to improve the security of automobile and intelligent, require that vehicle can identify the major obstacle thing (as vehicle) on road exactly, follow the tracks of, point out driver simultaneously, allow driver can grasp the situation of road in time, danger potential in driving procedure is made and judges accurately.
But highway and the road conditions of urban highway have obviously different.Usually, on highway, spacing is comparatively large, and road conditions are simpler, the change of the relative position such as objects in front (as vehicle, lane line) is little at short notice, and general spacing is less on urban highway, road conditions are complicated, and the rate of change of objects in front relative position is large.When changing little for Freeway Conditions, change between the successive frame that front end camera collection is returned is very little, under traditional detection algorithm, namely all processes each frame gathered, obviously like this, increase the weight of the unnecessary burden of processor, reduce real-time.And directly unnecessary frame is lost, under the complex road condition in urban district, obviously can not ensure its accuracy of detection.Therefore, in order to improve real-time and the high precision of guarantee detection, we need to apply different detection algorithms at highway and urban highway.But the prerequisite of realizing this goal accurately to judge that Current vehicle travels at highway or urban highway.So a kind of method proposing detection based on highway scene and automobile detecting following optimization is significant.
Summary of the invention
The object of the invention is to overcome the shortcoming of prior art and deficiency, a kind of method that detection based on highway scene and automobile detecting following are optimized is provided, the method accurately can judge that Current vehicle travels at highway or urban highway, improves real-time and the high precision of guarantee detection.
Object of the present invention is achieved through the following technical solutions: a kind of method that detection based on highway scene and automobile detecting following are optimized, and comprises the following steps:
1) detect the lane line in video, mark and record lane line information;
2) detect institute and mark vehicle in lane line, mark also recording information of vehicles;
3) detect the distance of vehicle in video, mark and record spacing D
i;
4) judge whether the distance of vehicle is greater than given threshold values D
thif had, then enter step 5), if do not had, then return step 1);
5) the spacing D in time t is recorded in
i, mark its maximal value D
maxwith minimum value D
min, and judge most value difference Δ=D
max-D
minwhether be less than set-point Δ
thif had, then enter step 6), if do not had, then return step 1);
6) judge that scene switches to highway;
7) marked vehicle is followed the tracks of.
Preferably, described step 1) in, the detection of lane line is based on randomized hough transform, finds two lane lines corresponding to Current vehicle traveling lane according to the constraint of lane line angle, and the lane line kept left is denoted as Line_L, the lane line of keeping right is denoted as Line_R; Video is by the monocular cam captured in real-time be arranged on vehicle, and camera is arranged on the position in the middle of vehicle front.
Further, described step 3) in, draw vehicle distances by data in frame of video, the process obtaining vehicle distances is as follows:
(1-1) method of rim detection positioning licence plate from video i-th frame is adopted;
(1-2) the length L of car plate is detected
1with vehicle distances L in video image
2;
(1-3) existing automotive license plate regular length is 440mm, by formula D
i=L
2 × 440/l
1mm extrapolates vehicle distances D
i.
Further, described step 7) in, be by following the tracks of near the direct position frame of video of vehicle being detected when detecting vehicle to the tracking of institute's marked vehicle, and the frame of video handled by following the tracks of is sampled with sampling rate fs from continuous print frame of video.
The present invention has following advantage and effect relative to prior art:
1, compared with prior art, the invention provides a kind of method based on highway scene detection, fill up the vacancy of prior art in highway scene detection.
2, the present invention utilizes spacing to realize the differentiation of highway and non-freeway two kinds of patterns.
3, the present invention is on the basis detecting highway scene, introduces the optimization method of automobile detecting following.When judging that scene has switched to highway, directly follow the tracks of near the position of frame of video vehicle being detected, and the frame of video handled by following the tracks of is sampled with sampling rate fs from continuous print frame of video, which reduce the process frame number of video, decrease calculated amount, improve real-time.
Accompanying drawing explanation
Fig. 1 is the schematic flow sheet of method of the present invention.
Embodiment
Below in conjunction with embodiment and accompanying drawing, the present invention is described in further detail, but embodiments of the present invention are not limited thereto.
Embodiment
As shown in Figure 1, a kind of method that detection based on highway scene and automobile detecting following are optimized, comprises the following steps:
Step 1, by being arranged on the monocular cam captured in real-time in the middle of vehicle front, get continuous print frame of video, pass through randomized hough transform, two lane lines corresponding to Current vehicle traveling lane are found according to the constraint of lane line angle, and the lane line kept left is denoted as Line_L, the lane line of keeping right is denoted as Line_R;
Step 2, detect institute and mark vehicle in lane line, mark is recording information of vehicles also, and method positioning licence plate from video i-th frame of employing rim detection, extrapolates vehicle distances D by the area S of license plate image
i, mark and record spacing D
i; Draw vehicle distances by data in frame of video, the process obtaining vehicle distances is as follows:
(1-1) method of rim detection positioning licence plate from video i-th frame is adopted;
(1-2) the length L of car plate is detected
1with vehicle distances L in video image
2;
(1-3) existing automotive license plate regular length is 440mm, by formula D
i=0.44L
2/l
1m extrapolates vehicle distances D
i.
Step 3, judge the distance D of vehicle
iwhether be greater than D
th=60m, if do not had, then enters step 2, if had, is recorded in the spacing D in time t=30s
i, mark its maximal value D
maxwith minimum value D
min, and judge most value difference Δ=D
max-D
minwhether be less than Δ
th=20m, if do not had, then returns step 2; If had, judge that scene switches to highway; Marked vehicle is followed the tracks of.
Sample with sampling rate fs from continuous print frame of video and process, directly following the tracks of near the position of frame of video vehicle being detected.
Above-described embodiment is the present invention's preferably embodiment; but embodiments of the present invention are not restricted to the described embodiments; change, the modification done under other any does not deviate from Spirit Essence of the present invention and principle, substitute, combine, simplify; all should be the substitute mode of equivalence, be included within protection scope of the present invention.
Claims (5)
1., based on the detection method of highway scene and an optimization for automobile detecting following, it is characterized in that, comprise the following steps:
Step 1, the lane line detected in video, mark and record lane line information;
Step 2, detect institute and mark vehicle in lane line, mark also recording information of vehicles;
In step 3, detection video, the distance of vehicle, marks and records spacing D
i;
Step 4, judge whether the distance of vehicle is greater than given threshold values D
th, if so, then enter step 5, otherwise, return step 1;
Step 5, the spacing D be recorded in time t
i, mark its maximal value D
maxwith minimum value D
min, and judge most value difference Δ=D
max-D
minwhether be less than set-point Δ
th, if so, then enter step 6, otherwise, return step 1;
Step 6, judgement scene switch to highway;
Step 7, marked vehicle to be followed the tracks of.
2. according to claim 1 based on the detection method of highway scene and the optimization of automobile detecting following, it is characterized in that, in step 1, the detection of described lane line is based on randomized hough transform, two lane lines corresponding to Current vehicle traveling lane are found according to the constraint of lane line angle, and the lane line kept left is denoted as Line_L, the lane line of keeping right is denoted as Line_R.
3. according to claim 1 based on the detection method of highway scene and the optimization of automobile detecting following, it is characterized in that, in step 1, described video is by the monocular cam captured in real-time be arranged on vehicle, and camera is arranged on the position in the middle of vehicle front.
4. according to claim 1ly to it is characterized in that based on the detection method of highway scene and the optimization of automobile detecting following, in step 3, protect vehicle distance be drawn by data in frame of video, the distance obtaining described vehicle comprises the following steps:
(1-1) method of rim detection positioning licence plate from video i-th frame is adopted;
(1-2) the length L of car plate is detected
1with vehicle distances L in video image
2;
(1-3) existing automotive license plate regular length is 440mm, by formula D
i=L
2 × 440/l
1mm extrapolates vehicle distances D
i.
5. according to claim 1 based on the detection method of highway scene and the optimization of automobile detecting following, it is characterized in that, in step 7, the described tracking to institute's marked vehicle is by following the tracks of near the direct position frame of video of vehicle being detected when detecting vehicle, and the frame of video handled by following the tracks of gets with sampling rate fs sampling from continuous print frame of video.
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CN109003338A (en) * | 2018-06-22 | 2018-12-14 | 南京慧尔视智能科技有限公司 | A kind of Roadside Parking self-clocking charging method and device |
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