CN103886745A - Automobile-dedicated lane early warning system - Google Patents
Automobile-dedicated lane early warning system Download PDFInfo
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- CN103886745A CN103886745A CN201310605990.7A CN201310605990A CN103886745A CN 103886745 A CN103886745 A CN 103886745A CN 201310605990 A CN201310605990 A CN 201310605990A CN 103886745 A CN103886745 A CN 103886745A
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Abstract
The invention discloses an automobile-dedicated lane early warning system, and aims at combing the fixed monitoring and the automobile-mounted monitoring to analyze and process road conditions and automobile conditions so that a real-time and accurate automobile-dedicated lane early warning system is realized. The automobile-dedicated lane early warning system comprises six steps of a video image acquisition step, an image preprocessing step, an edge detection step, a lane line detection step, an automobile detection and identification step and an alarm judgment step. The realization method of the aforementioned steps is that the video image acquisition step is performed via a camera. The image preprocessing step is performed on the acquired video image data. The edge detection step is performed on the preprocessed image data. The lane line detection step is performed according the result of the edge detection step. The automobile detection and identification step is performed according to the acquired image data. Finally the alarm judgment step is performed on the basis of integration of the lane line detection step and the automobile detection and identification step. If the detected automobile can be driven on the detected lane, alarm is not performed. If the detected automobile cannot be driven on the detected lane, alarm is performed.
Description
Technical field
The present invention relates to lane detection and vehicle identification field, more specifically a kind of to by point of fixity camera and vehicular camera collection to image analyze, the early warning system that the vehicles in lane line and track and object are carried out to detection and Identification.
Background technology
Along with the raising of people's living standard and the development of road traffic, the mode that people participate in road traffic also becomes more diverse, the kinds such as walking, bicycle, electric motor car, old scooter, private savings automobile and motorbus and quantity increase gradually, traffic safety problem is increasing, and the vehicle of increase on the impact of traffic also clearly.In city, be all provided with dedicated Lanes and alleviate traffic pressure, but there are some dedicated Lanes to be occupied by non-this track vehicle, in the situation that causing traffic congestion, also affected traffic safety and people's travel time simultaneously, have a strong impact on the unobstructed of the efficiency of road traffic and traffic system.In order to maintain harmonious traffic environment, vehicle can be taken their own roads, realize well-ordered state, the invention provides a kind of automobile specified track early warning system, it can be identified track, and detect non-this track object, the vehicle in some illegal encroachment automobile tracks is wanted to warn.
What before dedicated Lanes early warning detects, adopt is the mode of artificial law enforcement, but is faced with labor intensive, and workload is large, and under atrocious weather the difficult problem of people's cisco unity malfunction.Therefore, people begin one's study in real time, electronic communication supervisory system accurately and efficiently.Electronic monitoring and control system of today is divided into fixed electronic monitoring and control system and vehicular electronic monitoring and control system, fixed system can be monitored the situation in fixed area inside lane line, and the shortcoming of fixed system is also that it fixes, detection be limited in scope and single.Therefore there is vehicular dedicated Lanes warning system, this system is arranged on the current vehicle of dedicated Lanes, to front vehicles and Road Detection, if non-dedicated Lanes vehicle of the vehicle in front, record so and notify manually and intervene, this behavior is processed in time, kept smooth traffic.
Summary of the invention
For addressing the above problem, the invention discloses a kind of automobile specified track early warning system, object is in conjunction with fixed monitoring and vehicle-mounted monitoring, and road conditions and vehicle condition are carried out to analyzing and processing, thus realize one in real time, automobile specified track early warning system accurately.
The present invention takes following technical scheme to realize: a kind of automobile specified track early warning system, comprises video image acquisition, image pre-service, rim detection, lane detection, vehicle detection and identification and six steps that judge whether to report to the police, the implementation of above-mentioned steps is carried out video image acquisition step by camera, to the vedio data carries out image pre-treatment step collecting, pretreated view data is carried out to edge detecting step, carry out lane detection step according to the result of marginal test step, carry out vehicle detection and identification step according to the view data collecting, the result of last comprehensive lane detection and vehicle detection and two steps of identification is carried out the step that judges whether warning, if detected vehicle can, in detected lanes, not reported to the police, if detected vehicle cannot, in detected lanes, be reported to the police.
Realization of the present invention also comprises following technical scheme:
First above-mentioned lane detection step has adopted based on Gabor filtered method and has found end point, and the method then converting by Hough finds lane line, makes full use of the detection method based on model, by abstract problem be parameters calculation.This implementation has improved applicability and the real-time of this step.
Above-mentioned vehicle detection and identification step are divided into two steps: vehicle candidate region is detected and candidate region checking.The method based on knowledge is selected in the detection of candidate region, utilizes exactly the feature such as shape, color of vehicle, and some features of combining road are carried out the detection of vehicle candidate region.What the checking of candidate region was taked is the method based on outward appearance, and the method is divided according to the different characteristic of motor vehicle and bicycle, and main aspect comprises region area and the car plate of vehicle.
Advantage of the present invention and beneficial effect are embodied in the following aspects:
1. fixed and two kinds of monitoring modes of vehicular have been carried out effective combination by the present invention.
2. the vehicle detection in the present invention and identification step are identified vehicle according to the feature of vehicle, and carry out identification by stages, have improved the accuracy of identification vehicle.
3. the present invention can carry out early warning to the vehicle travelling in violation of rules and regulations effectively, has improved the security of road traffic, has brought convenience to people's trip.
Brief description of the drawings
Fig. 1 is execution step schematic diagram of the present invention;
Fig. 2 is Hough conversion schematic diagram;
Fig. 3 is Hough conversion schematic diagram;
Fig. 4 is lane detection steps flow chart schematic diagram;
Fig. 5 is vehicle detection and identification step schematic flow sheet.
Embodiment
Below in conjunction with Figure of description 1, enforcement of the present invention is further described:
A kind of automobile specified track early warning system, comprises video image acquisition, image pre-service, rim detection, lane detection, vehicle detection and identification and six steps that judge whether to report to the police, the implementation of above-mentioned steps is carried out video image acquisition step by camera, to the vedio data carries out image pre-treatment step collecting, pretreated view data is carried out to edge detecting step, carry out lane detection step according to the result of marginal test step, carry out vehicle detection and identification step according to the view data collecting, the result of last comprehensive lane detection and vehicle detection and two steps of identification is carried out the step that judges whether warning, if detected vehicle can, in detected lanes, not reported to the police, if detected vehicle cannot, in detected lanes, be reported to the police.
Below in conjunction with Figure of description 2, Figure of description 3 and Figure of description 4, the lane detection step in the present invention is further described:
At present, Chinese scholars has proposed the implementation procedure of a lot of lane detections, mainly be divided into two classes: a class is the detection method based on characteristics of image, what the method was some features based on road image by image is labeled as a little lane line point and non-lane line point, this method requires the lane line color of road comparatively obvious, edge is comparatively clear, otherwise cannot obtain testing result accurately; Another kind method is the detection method based on model, and it mates the lane line model pre-defining according to the feature of extracting, and the extraction of lane line is converted into the computational problem of lane line Model Parameter.First the present invention has adopted based on Gabor filtered method and has found end point, and the method then converting by Hough finds lane line, makes full use of the detection method based on model, by abstract problem be parameters calculation.
What traditional Hough conversion realized is a kind of mapping relations from image space to parameter space.Its essence is image is carried out to coordinate transform, make the result of conversion be easier to identification and detect.The polar coordinates expression formula of Hough conversion: ρ=xcos θ+ysin θ, wherein certain any coordinate of (x, y) representation space image, ρ is the distance of image space cathetus to true origin, θ is the angle of straight line and x axle, as shown in Figure of description 2.The range of choice of tradition Hough conversion voting space ρ and θ be generally ρ ∈ (0, r) (wherein r is image diagonal length), θ ∈ (0,180).As shown in Figure of description 3, the impact point of image space is carried out to coordinate transform and project to parameter space, by the more point of total ballot number of times in statistical parameter space, can find the straight-line equation that image space is corresponding.Conventionally can adjust by limiting ρ and θ the scope of its voting space, limit polar angle and the utmost point footpath scope of its left and right lane line, determine but region of perception.
Hough conversion is a kind of method for detecting lane lines of classics, has good applicability and robustness.But this algorithm is more consuming time, and the straight line existing in image space can only be detected, its some limitation such as end points and length can not be pointed out.
More consuming time for this implementation, to Hough, conversion improves in the present invention, has adopted the concept of area-of-interest (ROI).Limit the scope of its parameter space by limiting ρ and θ, limit polar angle and the utmost point footpath of lane line, obtain area-of-interest (ROI), removed a large amount of noise spots, improved the speed of algorithm.But in the time of turning, lane change or camera position skew, easily exceed monitored area, make result occur larger deviation.
For not pointing out the end points of lane line and the shortcoming of length, the present invention has adopted the lane detection method based on Gabor wave filter.The method finds the position of intersecting point of two lane lines by Gabor, namely the above-mentioned end point of mentioning, then carries out Hough conversion to it, obtains the straight line needing.This implementation has improved applicability and the real-time of this step.
Below in conjunction with Figure of description 5, the enforcement of vehicle detection in the present invention and identification step is further described:
After having determined the position and scope of lane line, next step is exactly the vehicle candidate region of determining in lane line, and judges whether the vehicle in motor vehicle diatom belongs to motor vehicle.The wide range containing due to motor vehicle, but with the difference of bicycle also clearly, so the present invention determines whether as motor vehicle according to the region area of vehicle and car plate.
Vehicle detection is divided into two steps: vehicle candidate region is detected and candidate region checking.Detection the present invention of candidate region selects the method based on knowledge, utilizes exactly the feature such as shape, color of vehicle, and some features of combining road are carried out the detection of vehicle candidate region.What the checking of candidate region was taked is the method based on outward appearance, and this implementation is divided according to the different characteristic of motor vehicle and bicycle, and main aspect comprises region area and the car plate of vehicle.
Because camera has certain coverage, distance object far away just seems less on image, so the region area of the vehicle near apart from camera will be larger, and far away will be less.Therefore can not fixed area area be divided by vehicle, the present invention selects multiple dimensioned method to carry out the detection of region area, the scope of taking is set up to three scopes: closely (in 5 meters), middle distance (5 to 10 meters), remote (10 to 20 meters).Different scopes, the region area of setting up is different.Distance is far away, and region area is smaller; Near distance, region area will more greatly, be set according to concrete analysis.
The present invention takes background frame difference method to obtain foreground target.With the background frames of present frame subtracting background acquisition module gained, then determine according to difference whether corresponding pixel is foreground moving target, determine foreground target with thresholding method.Carry out afterwards feature extraction, the region area to vehicle and car plate carry out feature extraction differentiation and classification.
Utilize technical solutions according to the invention, or those skilled in the art being under the inspiration of technical solution of the present invention, designs similar technical scheme, and reaching above-mentioned technique effect, is all to fall into protection scope of the present invention.
Claims (9)
1. an automobile specified track early warning system, is characterized in that: comprise video image acquisition, image pre-service, rim detection, lane detection, vehicle detection and identification and six steps that judge whether to report to the police, the implementation of above-mentioned steps is carried out described video image acquisition step by camera, the vedio data collecting is carried out to described image pre-treatment step, pretreated view data is carried out to described edge detecting step, carry out described lane detection step according to the result of marginal test step, carry out described vehicle detection and identification step according to the view data collecting, described in the result execution of two steps of last comprehensive described lane detection and described vehicle detection and identification, judge whether the step of reporting to the police, if detected vehicle can, in detected lanes, not reported to the police, if detected vehicle cannot, in detected lanes, be reported to the police.
2. a kind of automobile specified according to claim 1 track early warning system, is characterized in that: first described lane detection step has adopted based on Gabor filtered method and found end point, and the method then converting by Hough finds lane line.
3. lane detection step according to claim 2, it is characterized in that: the method for described Hough conversion is improved Hough conversion, adopt the concept of area-of-interest (ROI), limit the scope of its parameter space by limiting ρ and θ, limit polar angle and the utmost point footpath of lane line, obtain area-of-interest (ROI), removed a large amount of noise spots.
4. lane detection step according to claim 2, is characterized in that: described to find end point implementation based on Gabor filtered method be to find the position of intersecting point of two lane lines by Gabor.
5. a kind of automobile specified according to claim 1 track early warning system, is characterized in that: described vehicle detection and identification step are divided into two steps, and vehicle candidate region is detected and candidate region checking.
6. vehicle detection according to claim 5 and identification step, it is characterized in that: the method adopting based on knowledge is detected in described vehicle candidate region, utilize exactly the feature such as shape, color of vehicle, and some features of combining road are carried out the detection of vehicle candidate region.
7. vehicle detection according to claim 5 and identification step, it is characterized in that: the checking of described candidate region adopts the method based on outward appearance, this implementation is divided according to the different characteristic of motor vehicle and bicycle, and main aspect comprises region area and the car plate of vehicle.
8. candidate region according to claim 7 checking, it is characterized in that: the region area of described employing vehicle does not adopt fixed area area while carrying out vehicle division, the present invention selects multiple dimensioned method to carry out the detection of region area, the scope of taking is set up to three scopes: closely (in 5 meters), middle distance (5 to 10 meters), (10 to 20 meters) at a distance, different scopes, the region area of setting up is different; Distance is far away, and region area is smaller; Near distance, region area will more greatly, be set according to concrete analysis.
9. candidate region according to claim 7 checking, it is characterized in that: the region area of described employing vehicle and car plate carry out when vehicle is divided taking background frame difference method to obtain foreground target, with the background frames of present frame subtracting background acquisition module gained, then determine according to difference whether corresponding pixel is foreground moving target, determine foreground target with thresholding method, carry out afterwards feature extraction.
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Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104410838A (en) * | 2014-12-15 | 2015-03-11 | 成都鼎智汇科技有限公司 | Distributed video monitoring system |
| CN105741559A (en) * | 2016-02-03 | 2016-07-06 | 安徽清新互联信息科技有限公司 | Emergency vehicle lane illegal occupation detection method based on lane line model |
| CN105761525A (en) * | 2016-05-11 | 2016-07-13 | 南京信息职业技术学院 | System device for warning car to enter bus lane |
| CN106340180A (en) * | 2015-07-06 | 2017-01-18 | 北京文安智能技术股份有限公司 | Vehicle-mounted illegal lane occupation behavior detecting method and device |
| CN108470341A (en) * | 2017-02-23 | 2018-08-31 | 南宁市富久信息技术有限公司 | A kind of road edge detection method |
| CN111402609A (en) * | 2020-03-17 | 2020-07-10 | 北京百度网讯科技有限公司 | Special lane driving reminding method, device, equipment and storage medium |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102568212A (en) * | 2010-12-28 | 2012-07-11 | 沈阳聚德视频技术有限公司 | Intelligent detecting system of bus lane occupied by non-bus vehicle and control method thereof |
| CN103116748A (en) * | 2013-03-11 | 2013-05-22 | 清华大学 | Method and system for identifying illegal driving behavior based on road signs |
| CN103164958A (en) * | 2011-12-15 | 2013-06-19 | 无锡中星微电子有限公司 | Method and system for vehicle monitoring |
| CN103268471A (en) * | 2013-04-17 | 2013-08-28 | 深圳市锐明视讯技术有限公司 | Vehicle illegal land occupying detection method and device |
-
2013
- 2013-11-25 CN CN201310605990.7A patent/CN103886745A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102568212A (en) * | 2010-12-28 | 2012-07-11 | 沈阳聚德视频技术有限公司 | Intelligent detecting system of bus lane occupied by non-bus vehicle and control method thereof |
| CN103164958A (en) * | 2011-12-15 | 2013-06-19 | 无锡中星微电子有限公司 | Method and system for vehicle monitoring |
| CN103116748A (en) * | 2013-03-11 | 2013-05-22 | 清华大学 | Method and system for identifying illegal driving behavior based on road signs |
| CN103268471A (en) * | 2013-04-17 | 2013-08-28 | 深圳市锐明视讯技术有限公司 | Vehicle illegal land occupying detection method and device |
Non-Patent Citations (1)
| Title |
|---|
| 齐美彬 等: "一种快速的公交专用车道检测方法", 《微型机与应用》 * |
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104410838A (en) * | 2014-12-15 | 2015-03-11 | 成都鼎智汇科技有限公司 | Distributed video monitoring system |
| CN106340180A (en) * | 2015-07-06 | 2017-01-18 | 北京文安智能技术股份有限公司 | Vehicle-mounted illegal lane occupation behavior detecting method and device |
| CN105741559A (en) * | 2016-02-03 | 2016-07-06 | 安徽清新互联信息科技有限公司 | Emergency vehicle lane illegal occupation detection method based on lane line model |
| CN105741559B (en) * | 2016-02-03 | 2018-08-31 | 安徽清新互联信息科技有限公司 | A kind of illegal occupancy Emergency Vehicle Lane detection method based on track line model |
| CN105761525A (en) * | 2016-05-11 | 2016-07-13 | 南京信息职业技术学院 | System device for warning car to enter bus lane |
| CN108470341A (en) * | 2017-02-23 | 2018-08-31 | 南宁市富久信息技术有限公司 | A kind of road edge detection method |
| CN111402609A (en) * | 2020-03-17 | 2020-07-10 | 北京百度网讯科技有限公司 | Special lane driving reminding method, device, equipment and storage medium |
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Application publication date: 20140625 |