Multiple Features Fusion for Front-View Vehicle Detection

DOI

10.2991/aiie-15.2015.17How to use a DOI?

Keywords

rear-view vehicle; RGB color space; Otsu threshold segmentation

Abstract

With the rapid increase of vehicle holdings, urban transport is facing a severe test. Driver-assistance systems (ADAS) can effectively avoid happening of traffic accidents. Real-time detection of moving vehicle based on vision has become a research focus of ADAS. A method of multiple features fusion for front-view vehicle detection is proposed in this paper. Firstly, in RGB color space, license plate position is located using color conversion and Otsu threshold segmentation method is improved to confirm the vehicle’s candidate area. Secondly, geometrical characteristics of the license plate is adopted to eliminate distraction regions and to verify the extracted license plate. Finally, rear lamps of vehicle are detected and matched in candidate license plate regions, so vehicle area is further determined. The experimental results show that the proposed method in this paper can be used to detect vehicle in real-time and false detection rate is low.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - M.L. Men
AU  - F. Dai
PY  - 2015/07
DA  - 2015/07
TI  - Multiple Features Fusion for Front-View Vehicle Detection
BT  - Proceedings of the 2015 International Conference on Artificial Intelligence and Industrial Engineering
PB  - Atlantis Press
SP  - 59
EP  - 63
SN  - 1951-6851
UR  - https://doi.org/10.2991/aiie-15.2015.17
DO  - 10.2991/aiie-15.2015.17
ID  - Men2015/07
ER  -