Detection of Illegal U-turn Vehicles by Optical Flow Analysis 


Vol. 39,  No. 10, pp. 948-956, Oct.  2014


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  Abstract

Today, Intelligent Vehicle Detection System seeks to reduce the negative factors, such as accidents over to get the traffic information of existing system. This paper proposes detection algorithm for the illegal U-turn vehicles which can cause critical accident among violations of road traffic laws. We predicted that if calculated optical flow vectors were shown on the illegal U-turn path, they would be cause of the illegal U-turn vehicles. To reduce the high computational complexity, we use the algorithm of pyramid Lucas-Kanade. This algorithm only track the key-points likely corners. Because of the high computational complexity, we detect center lane first through the color information and progressive probabilistic hough transform and apply to the around of center lane. And then we select vectors on illegal U-turn path and calculate reliability to check whether vectors is cause of the illegal U-turn vehicles or not. Finally, In order to evaluate the algorithm, we calculate process time of the type of algorithm and prove that proposed algorithm is efficiently.

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  Cite this article

[IEEE Style]

C. Song and J. Lee, "Detection of Illegal U-turn Vehicles by Optical Flow Analysis," The Journal of Korean Institute of Communications and Information Sciences, vol. 39, no. 10, pp. 948-956, 2014. DOI: .

[ACM Style]

Chang-ho Song and Jaesung Lee. 2014. Detection of Illegal U-turn Vehicles by Optical Flow Analysis. The Journal of Korean Institute of Communications and Information Sciences, 39, 10, (2014), 948-956. DOI: .

[KICS Style]

Chang-ho Song and Jaesung Lee, "Detection of Illegal U-turn Vehicles by Optical Flow Analysis," The Journal of Korean Institute of Communications and Information Sciences, vol. 39, no. 10, pp. 948-956, 10. 2014.

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pISSN : 1226 - 4717
eISSN : 2287 - 3880