Low-illumination environment vehicle detection based on optimized adaptive image enhancement

Kun Zhao; Jian Liu; Xiaocheng Xiao

doi:10.1117/12.2608155

11 November 2021 Low-illumination environment vehicle detection based on optimized adaptive image enhancement

Kun Zhao, Jian Liu, Xiaocheng Xiao

Proceedings Volume 12076, 2021 International Conference on Image, Video Processing, and Artificial Intelligence; 1207607 (2021) https://doi.org/10.1117/12.2608155
Event: Fourth International Conference on Image, Video Processing, and Artificial Intelligence (IVPAI 2021), 2021, Shanghai, China

Abstract

With the increasing number of vehicles, vehicle detection has become an important part of intelligent transportation system. At present, most detection algorithms are only suitable for normal light conditions, but the detection performance is poor for low illumination conditions. In order to achieve effective vehicle detection under low illumination conditions, this paper proposes an image enhancement algorithm to increase the contrast of the image, thereby greatly improving the effect of vehicle detection. First, the image contrast is enhanced through an adaptive contrast stretching algorithm. Secondly, the bilateral filtering algorithm is used to filter out the noise in the image. Finally, the detection system based on Haar features and AdaBoost classifier is used to detect vehicles. Experimental results show that the proposed algorithm can effectively enhance image contrast, highlight vehicle information, and the vehicle detection accuracy rate under low illumination conditions reaches 87.04%.

Citation Download Citation

Kun Zhao, Jian Liu, and Xiaocheng Xiao "Low-illumination environment vehicle detection based on optimized adaptive image enhancement", Proc. SPIE 12076, 2021 International Conference on Image, Video Processing, and Artificial Intelligence, 1207607 (11 November 2021); https://doi.org/10.1117/12.2608155

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