CN102542805A - Device for judging traffic jam based on videos - Google Patents
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- CN102542805A CN102542805A CN2012100609129A CN201210060912A CN102542805A CN 102542805 A CN102542805 A CN 102542805A CN 2012100609129 A CN2012100609129 A CN 2012100609129A CN 201210060912 A CN201210060912 A CN 201210060912A CN 102542805 A CN102542805 A CN 102542805A
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Abstract
The invention belongs to the technical field of video detection and image recognition and discloses a device for judging a traffic jam based on videos. The device mainly comprises a camera, a video detection system, a video analysis system and a jam promoting system, wherein the camera acquires road traffic video images; video image information is transmitted to the video detection system for background modeling, foreground extraction and vehicle identification, and then is transmitted to the video analysis system for analysis of the jam condition; and finally the jam condition is transmitted to the jam prompting system for prompting. By judging a road traffic state, the detection precision is improved, and the performance of video monitoring is improved.
Description
Technical field
The invention belongs to Video Detection and image recognition technology field, relate more specifically to a kind of device of judging traffic congestion based on video.
Background technology
In recent years, along with the fast development of world economy, the traffic loading sharp increase, problem such as thing followed road is crowded serious, traffic hazard takes place frequently has progressively become the principal element of restriction various countries' transport development.Therefore, in time correctly carrying out the road traffic differentiation of blocking up, is to take reasonable early warning measure, initiatively avoid the prerequisite of traffic congestion, also can reference be provided for public's trip and urban transportation scheduling simultaneously, is the effective means that improves road passage capability.
The existing technology of analyzing the urban road traffic congestion situation mainly contains: toroid winding method, radar (microwave) method, supercritical ultrasonics technology, based on the GPS Data Act etc.; Wherein the toroid winding method in use also progressively manifests some fatal shortcomings; As need be on the road surface when inductive coil is installed grooving; Recharge coating after the installation, destroy the integrality on road surface, influence pavement life.Need suspend traffic when safeguarding inductive coil, and can not detect stationary vehicle.The appeal method cuts both ways, and all can not realize accurately, detect in real time, easily road traffic condition.
Along with the progressively development of technology, present road traffic differentiation develops into mainly carries out analyzing and processing based on floating car data, is aided with food monitoring resources a large amount of in the city and with the means of artificial observation road traffic state is revised and replenished.But the accuracy that is based on the traffic state judging algorithm of floating car data has direct related with Floating Car quantity and operation state; So can't reach very high accuracy; The method of artificial observation video monitoring then has has high requirement to the observation people, has the too subjective and higher rate of failing to report of distinguishing rule.So, be necessary advanced person's video detection technology reasonably is applied to China's field of traffic for the existing video monitoring resource of more efficient use.
Video detection technology is also not very long in the developing history of the applied research of field of traffic, and 1984, the University of Minnesota of the U.S. carried out the research that computer vision is applied to senior traffic administration first.1984 to 1989, further experimental study was done by this university under the fostering of traffic department, had set up ISS (Image Sensing System) company simultaneously for this reason, specialized in the exploitation of traffic video technology.In 1987, ISS company designed first prototype, and the application of video detection technology at field of traffic at first verified in design this time.
The research of video detection technology its domestic application is started late; Be accompanied by the development of communications and transportation, the application demand of traffic administration and control is in continuous increase, and domestic many companies have also done many effort in this respect; But it is perfect inadequately that product rests on the function of level or realization of prototype mostly; Effect and not obvious also is far from reaching requirement of actual application in the middle of the popularization of reality, compares with external product to also have suitable gap.
To sum up; Road traffic state differentiation based on video monitoring also has many weak points; It is high and still rest on the aspect of DETECTION OF TRAFFIC PARAMETERS to be mainly reflected in accuracy of detection; Also need further traffic parameter to be carried out analyzing and processing if will differentiate road traffic state, do not give full play of the due performance of video monitoring.
Summary of the invention
1. technical matters to be solved by this invention.
For improving the differentiation of road traffic state, increase accuracy of detection, improve the performance of video monitoring, proposed to judge the device of traffic congestion based on video.
2. the technical scheme that addresses the above problem of the present invention.
The present invention mainly comprises video camera, video detection system, video analytic system, prompt system blocks up.Video camera obtains the road traffic video image; Video image information is transferred to video detection system to carry out being transferred to video analytic system after background modeling, foreground extraction, the vehicle identification and carries out the jam situation analysis, at last jam situation is transferred to the prompt system that blocks up and points out.
Video detection system comprises time-space domain background modeling module, extracts foreground information module, connected domain analysis module.
Time-space domain background module adopts mixed Gauss model to set up the time-and-space background model of video monitoring image.
Extract the foreground information module and calculate the similarity of current figure and time-space domain background model, extract foreground information.
The connected domain analysis module extracts the characteristic information of the connected domain in the foreground information.
Video analytic system obtains the data of connected domain analysis module output, utilizes the distance of connected domain and area information to carry out vehicle identification.
The connected domain analysis module analyzes if no car then upgrades current video, if there is car then to extract the characteristic information of connected domain.
Video analytic system calculates the average velocity of different target in time period 1, and the mean value of all car speeds and configures the speed threshold values as the speed parameter of current road on the computed image.
Video analytic system judges that when speed parameter then is transferred to the prompt system that blocks up greater than the speed threshold values be unimpeded signal, if speed parameter then is transferred to the prompt system that blocks up less than the speed threshold values and is the signal that blocks up.
The prompt system that blocks up has sound prompt function.
The present invention carries out the differentiation of road traffic state through video image, increases accuracy of detection, improves the performance of video monitoring.
Description of drawings
Fig. 1 is a system construction drawing of the present invention.
Fig. 2 is the structural drawing of video detection system of the present invention.
Embodiment
For clear statement implementation process of the present invention, the specific embodiment of judging the device of traffic congestion based on video is described step by step below.
Background modeling in the video detection system is to utilize mixed Gaussian background modeling method to set up the time domain background model of each pixel; Carry out the adaptively selected of gauss component number; When specifically comprising initialization, the mixed Gauss model of each pixel of scene only is provided with a gauss component, when scene changes; When the mixed Gauss model of pixel can not mate with current pixel; If the gauss component number in this pixel mixed Gauss model does not reach the maximal value of setting, then increasing by one automatically is the initial gauss component of average with the currency, otherwise uses current pixel value to replace the end gauss component in the pixel mixed Gauss model as the new gauss component of average.After model modification is accomplished; Judge whether last gauss component in the mixed Gauss model of each pixel is expired; If it is expired then deletion through the analysis of time domain background model to scene, has obtained one group of sample of expression background; The directly sample distribution spatially of these expression backgrounds of statistics is as the spatial domain background model of pixel.
The connected domain analysis module extracts the characteristic information of the connected domain in the foreground information.At first remove the noise influence in the foreground information; Object pixel is transformed into the connected component level; Utilize the expansive working number to remove the aperture of filling up the target area, again the result is turned back on the initial prospect point set again, recover the intrinsic edge of foreground image; Extract the number of connected domain in the statistical picture then and, extract area, girth, position of form center and the boundary rectangle information of connected domain at last each connected component labeling.
Video analytic system obtains the data of connected domain analysis module output, utilizes the distance of connected domain and area information to carry out vehicle identification.
The connected domain analysis module analyzes if no car then upgrades current video, if there is car then to extract the characteristic information of connected domain.
Video analytic system calculates the average velocity of different target in time period 1, and the mean value of all car speeds and configures the speed threshold values as the speed parameter of current road on the computed image.
Video analytic system judges that when speed parameter then is transferred to the prompt system that blocks up greater than the speed threshold values be unimpeded signal, if speed parameter then is transferred to the prompt system that blocks up less than the speed threshold values and is the signal that blocks up.
The prompt system that blocks up has sound prompt function.
The foregoing description does not limit the present invention in any way, and every employing is equal to the technical scheme that replacement or the mode of equivalent transformation obtain and all drops in protection scope of the present invention.
Claims (10)
1. judge based on video and the device of traffic congestion it is characterized in that comprising following a few part for one kind: mainly comprise video camera, video detection system, video analytic system, prompt system blocks up; Video camera obtains the road traffic video image; Video image information is transferred to video detection system to carry out being transferred to video analytic system after background modeling, foreground extraction, the vehicle identification and carries out the jam situation analysis, at last video Data Transmission is pointed out to the prompt system that blocks up.
2. the device based on video judgement traffic congestion according to claim 1 is characterized in that: video detection system comprises time-space domain background modeling module, extracts foreground information module, connected domain analysis module.
3. according to claim 1 and 2 described devices based on video judgement traffic congestion, it is characterized in that: time-space domain background module adopts mixed Gauss model to set up the time-and-space background model of video monitoring image.
4. according to claim 1 and 2 described devices, it is characterized in that: extract the similarity that the foreground information module is calculated current figure and time-space domain background model, extract foreground information based on video judgement traffic congestion.
5. according to claim 1 and 2 described devices based on video judgement traffic congestion, it is characterized in that: the connected domain analysis module extracts the characteristic information of the connected domain in the foreground information.
6. the device based on video judgement traffic congestion according to claim 1, it is characterized in that: video analytic system obtains the data of connected domain analysis module output, utilizes the distance of connected domain and area information to carry out vehicle identification.
7. according to claim 1 and 5 described devices based on video judgement traffic congestion, it is characterized in that: the connected domain analysis module analyzes if no car then upgrades current video, if there is car then to extract the characteristic information of connected domain.
8. the device of judging traffic congestion based on video according to claim 1; It is characterized in that: video analytic system calculates the average velocity of different target in time period 1; The mean value of all car speeds is as the speed parameter of current road on the computed image, and configures the speed threshold values.
9. according to claim 1 and the 8 described devices of judging traffic congestion based on video; It is characterized in that: video analytic system judges that when speed parameter then is transferred to the prompt system that blocks up greater than the speed threshold values be unimpeded signal, if speed parameter then is transferred to the prompt system that blocks up less than the speed threshold values and is the signal that blocks up.
10. the device based on video judgement traffic congestion according to claim 1, it is characterized in that: the prompt system that blocks up has sound prompt function.
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| CN102867415A (en) * | 2012-09-12 | 2013-01-09 | 重庆大学 | Video detection technology-based road jam judgement method |
| CN105447479A (en) * | 2015-12-29 | 2016-03-30 | 安徽海兴泰瑞智能科技有限公司 | Traffic state video monitoring method for high-speed bayonet road |
| CN108564791A (en) * | 2018-06-13 | 2018-09-21 | 新华网股份有限公司 | Information processing method, device and computing device |
| CN108682154A (en) * | 2018-06-19 | 2018-10-19 | 上海理工大学 | Congestion in road detecting system based on the analysis of wagon flow state change deep learning |
| CN108898790A (en) * | 2018-09-07 | 2018-11-27 | 广东华诚电力设计有限公司 | Monitoring system after a kind of project of electric power base station |
| CN110920624A (en) * | 2019-12-09 | 2020-03-27 | 广东飞达交通工程有限公司 | Road congestion real-time prediction method, equipment and system based on vehicle networking |
| CN113362605A (en) * | 2021-07-23 | 2021-09-07 | 上海交通大学 | Distributed traffic flow optimization system and method based on potential homogeneous region identification |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102867415A (en) * | 2012-09-12 | 2013-01-09 | 重庆大学 | Video detection technology-based road jam judgement method |
| CN102867415B (en) * | 2012-09-12 | 2015-05-13 | 重庆大学 | Video detection technology-based road jam judgement method |
| CN105447479A (en) * | 2015-12-29 | 2016-03-30 | 安徽海兴泰瑞智能科技有限公司 | Traffic state video monitoring method for high-speed bayonet road |
| CN108564791A (en) * | 2018-06-13 | 2018-09-21 | 新华网股份有限公司 | Information processing method, device and computing device |
| CN108682154A (en) * | 2018-06-19 | 2018-10-19 | 上海理工大学 | Congestion in road detecting system based on the analysis of wagon flow state change deep learning |
| CN108898790A (en) * | 2018-09-07 | 2018-11-27 | 广东华诚电力设计有限公司 | Monitoring system after a kind of project of electric power base station |
| CN110920624A (en) * | 2019-12-09 | 2020-03-27 | 广东飞达交通工程有限公司 | Road congestion real-time prediction method, equipment and system based on vehicle networking |
| CN113362605A (en) * | 2021-07-23 | 2021-09-07 | 上海交通大学 | Distributed traffic flow optimization system and method based on potential homogeneous region identification |
| CN113362605B (en) * | 2021-07-23 | 2022-06-21 | 上海交通大学 | Distributed highway optimization system and method based on potential homogeneous area analysis |
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Application publication date: 20120704 |