Dual Tree Complex Wavelet Transform based Shadow Detection and Removal from Moving Objects

摘要

Presence of shadow degrades performance of any computer vision system as a number of shadow points are always misclassified as object points. Various algorithms for shadow detection and removal exist for still images but very few algorithms have been developed for moving objects. This paper introduces a new method for shadow detection and removal from moving object which is based on Dual tree complex wavelet transform. We have chosen Dual tree complex wavelet transform as it is shift invariant and have a better edge detection property as compared to real valued wavelet transform. In the present work, shadow detection and removal has been done by thresholding wavelet coefficients of Dual tree complex wavelet transform of difference of reference frame and the current frame. Standard deviation of wavelet coefficients is used as an optimal threshold. Results after visual and quantitative performance metrics computation shows that the proposed method for shadow detection and removal is better than other state-of-the- art methods.