Computer Science and Information Systems 2010 Volume 7, Issue 1, Pages: 201-210
https://doi.org/10.2298/CSIS1001201D
Full text ( 232 KB)
Cited by


Robust moving object detection under complex background

Ding Ying (School of Computer Science and Technology, Jilin University, Changchun, China + School of Computer Science and Technology, Changchun University of Science and Technology, Changchun, China)
Wen-Hui Li (School of Computer Science and Technology, Jilin University, Changchun, China)
Jing-Tao Fan (School of Computer Science and Technology, Changchun University of Science and Technology, Changchun, China)
Hua-Min Yang (School of Computer Science and Technology, Changchun University of Science and Technology, Changchun, China)

We present a novel method to robustly and efficiently detect moving object, even under the complexity background, such as illumination changes, long shadows etc. This work is distinguished by three key contributions. The first is the integration of the Local Binary Pattern texture measure which extends the moving object detection work for light illumination changing. The second is the introduction of HSI color space measure which removes shadows for the background subtraction. The third contribution is a novel fuzzy way using the Choquet integral which improves detection accuracy. The experiment results using several dataset videos show the robustness and effectiveness of the proposed method.

Keywords: moving object detection, Local Binary Pattern, HSI, Choquet integral