Robust vehicle detection for highway surveillance via rear-view monitoring

Akio Yoneyama; Chia-Hung Yeh; C.-C. Jay Kuo

doi:10.1117/12.504094

19 November 2003 Robust vehicle detection for highway surveillance via rear-view monitoring

Akio Yoneyama, Chia-Hung Yeh, C.-C. Jay Kuo

Proceedings Volume 5203, Applications of Digital Image Processing XXVI; (2003) https://doi.org/10.1117/12.504094
Event: Optical Science and Technology, SPIE's 48th Annual Meeting, 2003, San Diego, California, United States

Abstract

Vision-based highway monitoring systems play an important role in transportation management and services owing to their powerful ability to extract a variety of information. Detection accuracy of vision-based systems is however sensitive to environmental factors such as lighting, shadow and weather conditions, and it is still a challenging problem to maintain detection robustness at all time. In this research, we present a novel method to enhance detection and tracking accuracy at the nighttime based on rear-view monitoring. In the meanwhile, a method is proposed to improve the background detection and extraction, which usually serves as the first step to moving object region detection. Finally, the effectiveness of the rear-view technique will be analyzed. We compare the tracking accuracy between the front-view and the rear-view techniques, and show that the proposed system can achieve higher detection accuracy at nighttime.

Citation Download Citation

Akio Yoneyama, Chia-Hung Yeh, and C.-C. Jay Kuo "Robust vehicle detection for highway surveillance via rear-view monitoring", Proc. SPIE 5203, Applications of Digital Image Processing XXVI, (19 November 2003); https://doi.org/10.1117/12.504094

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