Title: Research on visual background extractor to identify the vehicles based on edge similarity

Authors: Yong Liu; Daopin Xia; Qinjun Qiu; Dawei Cai

Addresses: College of Computer and Information Technology, China Three Gorges University, Yichang, Hubei 443002, China ' College of Science and Technology, China Three Gorges University, Yichang, China ' Institute of Intelligent Vision and Image Information, China Three Gorges University, Yichang, China ' Institute of Intelligent Vision and Image Information, China Three Gorges University, Yichang, China

Abstract: By combining visual background extractor with Canny operator, a new approach to identify vehicles in a complex traffic environment is proposed. Firstly, the foreground object is extracted by ViBe algorithm and background difference algorithm, then the 'ghost' is removed by means of edge similarity. Next, the complete moving objects can be obtained by using morphological processing for the foreground object, which can be used to detect vehicles by combining with motion analysis. Experiments showed that the whole region of the vehicle object in a complex traffic environment can be extracted exactly and effectively by using this method. In addition, problems due ghosts and the variation of background can be well handled with low computation complexity, which can fulfil the needs of real-time operation.

Keywords: vehicle detection; ViBe algorithm; ghost; motion analysis.

DOI: 10.1504/IJWMC.2017.087357

International Journal of Wireless and Mobile Computing, 2017 Vol.13 No.1, pp.8 - 14

Received: 22 Dec 2016
Accepted: 06 Apr 2017
Published online: 13 Oct 2017 *

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