Robust object segmentation using probability-based background extraction algorithm

Authors:
Chung-Cheng Chiu;Li-wey Liang;Min-Yu Ku;Bing-Fei Wu;Yuh-Chyun Luo
Affiliations:
National Defense University, Dashi Jen, Taoyuan, Taiwan;National Defense University, Dashi Jen, Taoyuan, Taiwan;National Defense University, Dashi Jen, Taoyuan, Taiwan;National Chiao Tung University, Dashi Jen, Taoyuan, Taiwan;National Defense University, Dashi Jen, Taoyuan, Taiwan
Venue:
GVE '07 Proceedings of the IASTED International Conference on Graphics and Visualization in Engineering
Year:
2007

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Abstract

This paper proposes a robust object segmentation by the means of the probability-based background extraction algorithm. The color background images can be extracted efficiently and quickly from color image sequences by the proposed background extraction algorithm. After the background extraction algorithm, the intrusive objects can be segmented correctly and immediately by the robust object segmentation. The background extraction algorithm calculates the color probabilities of each pixel and uses a convergent value to decide the background pixel color, whose probability is the maximum one and greater than the convergent value. The extracted background is updated in real-time to overcome the variation of the illuminative condition. Experimental results using different types of video sequences are presented to demonstrate the robustness, accuracy, and time responses of the proposed algorithm.