2012 Volume 132 Issue 10 Pages 857-863
Background subtraction is a method typically used to segment moving vehicles in image sequences taken from a static camera by comparing each new frame with a model of the background scene. This paper presents a robust background subtraction algorithm which reduces the influence of illumination changes and shadows and adapts to rapid changes in the traffic scene. A statistical background modeling method is presented, which is based on a histogram at the pixel level and produces a color model from a series of frames. For foreground detection, we propose the Choquet integral to fuse the three color-component similarity measures and a texture similarity measure based on a uniform local binary pattern. Finally, we propose a new adaptive background maintenance method. The experimental results for several dataset videos show that the proposed method is more efficient, robust, and accurate than classical approaches.
The transactions of the Institute of Electrical Engineers of Japan.A
The Journal of the Institute of Electrical Engineers of Japan