Moving Shadow Removal Based on YCbCr Color Space and Weighted Local-texture Analysis
Zheng Yin · Computer Knowledge and Technology · 2013
In order to solve the difficulties of extracting the wrong traffic parameters that caused by the accuracy of shadow de tecting methods in traditional intelligence traffic system,a method of shadow detection and removal is proposed based on YCbCr color space and Local Fourier transform( LFT). Firstly, analyse the intensity and chromacity characteristics of the YCbCr color space to obtain the rough regions of the shadows, Secondly, use the texture discrimination performance of LFT coefficients even moments and weighted cross-entropy method for moving shadow removal exactly in video sequences. Experiments on different scenes suggest that effective detection rate of proposed method is over 85.3 percent, and can satisfy the requirement of real-time processing, and set a good foundation for the extracting of traffic parameters.