Reliable moving vehicle detection based on the filtering of swinging tree leaves and raindrops

Authors:
Deng-Yuan Huang;Chao-Ho Chen;Wu-Chih Hu;Sing-Syong Su
Affiliations:
Department of Electrical Engineering, Dayeh University, 168 University Rd., Dacun, Changhua 515, Taiwan, ROC;Department of Electronic Engineering, National Kaohsiung University of Applied Sciences, 415, Chien Kung Rd., Kaohsiung 807, Taiwan, ROC;Department of Computer Science and Information Engineering, National Penghu University of Science and Technology, 300 Liu-Ho Rd., Makung, Penghu 880, Taiwan, ROC;Department of Electronic Engineering, National Kaohsiung University of Applied Sciences, 415, Chien Kung Rd., Kaohsiung 807, Taiwan, ROC
Venue:
Journal of Visual Communication and Image Representation
Year:
2012

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Abstract

An efficient method for detecting moving vehicles based on the filtering of swinging trees and raindrops is proposed. To extract moving objects from the background, an adaptive background subtraction scheme with a shadow elimination model is used. Swinging trees are removed from foreground objects to reduce the computational complexity of subsequent tracking. Raindrops are removed from foreground objects when necessary. Performance evaluations are carried out using seven real-world traffic image sequences. Experimental results show average recognition rates of 96.83% and 97.20% for swinging trees and raindrops, respectively, indicating the feasibility of the proposed method.