Vehicle Detection and Tracking Based on GMM and Enhanced Camshift Algorithm
Journal of Electrical and Electronic Engineering
Volume 6, Issue 2, April 2018, Pages: 40-45
Received: Apr. 26, 2018; Published: Apr. 27, 2018
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Kaiyang Zhong, Department of Software Engineering, Xiamen University, Xiamen, China
Zhaoyang Zhang, Department of Software Engineering, Xiamen University, Xiamen, China
Zhengyu Zhao, Department of Software Engineering, Xiamen University, Xiamen, China
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Vehicle detection and tracking is an important part of the intelligent transportation system. With the rapid development of computer vision, video based vehicle detection and tracking technology has become a hot topic. In this paper, on the foundation of the present work, an enhanced detection tracking algorithm is proposed based on the popular Gauss mixture model(GMM) and Camshift. First, GMM is used to extract the foreground, and then the morphological operations is carried out to enhance the image, so that to remove the random noises. Finally, enhanced Camshift is designed to track the vehicle which is discussed in detail below. The experimental results demonstrate that the tracking accuracy can be improved.
Vehicle Detection, Vehicle Tracking, GMM, Camshift
To cite this article
Kaiyang Zhong, Zhaoyang Zhang, Zhengyu Zhao, Vehicle Detection and Tracking Based on GMM and Enhanced Camshift Algorithm, Journal of Electrical and Electronic Engineering. Vol. 6, No. 2, 2018, pp. 40-45. doi: 10.11648/j.jeee.20180602.11
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