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Traffic jam detection method based on video processing

A detection method and video processing technology, which is applied in the field of traffic congestion detection based on video analysis technology, can solve problems such as unsatisfactory vehicle tracking effects, and achieve the effect of assisting in judging traffic congestion status, accurate results, and improving accuracy

Inactive Publication Date: 2011-11-23
崔志明 +3
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the intensity of the light, the speed of the vehicle and the occlusion of the vehicle make the vehicle tracking effect not ideal.

Method used

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  • Traffic jam detection method based on video processing
  • Traffic jam detection method based on video processing
  • Traffic jam detection method based on video processing

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0039] Example one: figure 1 It is a flowchart of a method for detecting traffic congestion based on video analysis technology implemented in the present invention, and the data file is a video file containing moving vehicles.

[0040] Step 1: Use the multi-frame image averaging method to obtain the background image of the video surveillance area. Since an increase in the average number of frames will improve the effect of noise elimination, the preferred technical solution is to read in in advance 500 consecutive video images for averaging.

[0041] Step 2: Set up a virtual detection line perpendicular to the driving direction of the vehicle at the edge of the surveillance area where the vehicle enters and exits in the video image. When the vehicle in the video passes through the virtual detection line, the image pixel value at the detection line position will change due to the coverage of the vehicle. When the width of the moving object covering the detection line is greater tha...

Embodiment 2

[0073] Embodiment 2: To illustrate the preference of the H, S, and V block parameters of the HSV histogram in Embodiment 1, this example uses the histogram hue H of the HSV color space to be divided into 8 parts, and the saturation S and the brightness V are respectively Divided into 3 parts. Select the video in the first embodiment, and evaluate the traffic jam state according to the same specific implementation steps. The recognition rates are 91.57% in unblocked state, 89.63% in lightly congested state, 87.26% in congested state, and 89.80% in severely congested state. Basically, various congestion states can also be recognized, but the recognition rate of various congestion states is lower than the first embodiment.

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Abstract

The invention discloses a traffic jam detection method based on a video analysis technology. Based on video segmentation and key frame extraction, traffic jam detection is realized by acquiring three jam characteristic quantities, namely average dissimilarity of a video lens, key frame number and average optical flow field energy and adopting a multi-class support vector machine (SVM) method. By using the new traffic jam detection method provided by the invention, the problem of difficulty in completely or accurately acquiring traffic parameters such as traffic volume, vehicle speed, density and the like in the prior art is avoided, the running locus of a vehicle does not need to be tracked, the result of detecting the traffic jam state is more accurate, and the method can be used for well assisting the traffic department in knowing about the traffic jam state.

Description

Technical field [0001] The invention belongs to the field of digital video processing, and specifically relates to a method for detecting traffic congestion based on video analysis technology. Background technique [0002] With the development of social economy and urbanization, the number of motor vehicles has increased rapidly, and the problem of urban traffic congestion has become increasingly serious. Timely and correctly judging the state of road traffic congestion is a prerequisite for adopting reasonable traffic congestion warning and inducing vehicles to carry out reasonable road allocation to actively avoid traffic congestion. Therefore, the automatic road congestion identification method (ACI) for the purpose of discovering the traffic congestion state on the road has become one of the important areas in the research of intelligent transportation systems. [0003] At present, video surveillance technology has entered the stage of full digitalization and networking. The ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G08G1/01G06K9/00G06K9/62
Inventor 崔志明杨元峰吴健张广铭岳恒军
Owner 崔志明
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