Video Vehicle Detection Method Based on Multiple Color Space Information Fusion

Abstract:

A detection method which selective fuses the nine detection results of RGB, YCbCr and HSI color space according to the image color space relative independence of each component and complementarities is approached in order to improve vehicle video detection accuracy. The method fuses three different detection results in nine components by the value of H when the value of both S and I are higher and does another three detection results when the value of both S and I are smaller. Experiments show that the method compared to the traditional method using only the detection results of the brightness component improved substantial, reduced empty of the detected vehicle a large extent and increased traffic information data accuracy depending on the detection result.

• Periodical: Advanced Materials Research (Volumes 546-547)
• Pages: 721-726
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.546-547.721
• Online since: July 2012
• Authors: Hong Xiang Shao, Xiao Ming Duan
• Keywords: Information Fusion, Multiple Color Spaces, Vehicle Detection Introduction

References

[1] L IPTON AJ, FUJIYOSH IH, PATIL R S. Moving target classification and tracking from real2time video [C]. WACVp98: Proceedings of the 4th IEEE Workshop on Applications of Computer Vision. Washington, DC: IEEE Computer Society, 1998: 8 - 14.

DOI: 10.1109/acv.1998.732851

[2] HAR ITAOGLU I, HARWOOD D, DAV IS L S. W4: real2time surveillance of people and their activities [J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2000, 22 (8) : 809 - 830.

DOI: 10.1109/34.868683

[3] ZHANG Zhong-fang, LI Jin-ping, Bai Pei. Mobile Object Detection Algorithm Based on Information Fusion of Multiple Color Spaces[J]. Journal of University of Jinan (Science and Technology), 2011, 25(2), 192-195.

[4] Ohta N. A statistical approach to background subtraction for surveillance systems. Computer Vision, 2000, ICCV 2001, Proceedings, Eighth IEEE International Conference, 2001, 2(2): 481-486.

DOI: 10.1109/iccv.2001.937664

[5] Ying Ren, Chin-Seng Chua, Yeong-Khing H. Motion detection with non-stationary background Image Analysis and Processing, 2001, Proceedings, 11th International Conference, 2001: 78-83.

DOI: 10.1109/iciap.2001.956988

[6] DING Tianhuai, JIA Dongyao. Detection of similar targets using multiple color space feature fusion［J］. Journal of Tsinghua University(Science and Technology), 2006，46(2)：176 -179.

[7] FENG Xiao-hui, WANG Wei-ning, WU Xu-zhen. Adaptive mouth region detection algorithm based on multi-color spaces［J］. Journal of Computer Applications，2009，7：48 - 51.

DOI: 10.3724/sp.j.1087.2009.01924

[8] CHAPRON M. A new chromatic edge detectorused for color image segmentation [C]. Proceedings of the 11th IAPR International Conference on Pattern Recognition. Washington, D C: IEEE Computer Society, 1992: 311 - 314.

DOI: 10.1109/icpr.1992.201987