A novel vehicle's shadow detection and removal algorithm

Abstract

In outdoor vehicles detection system based on video signal processing, the shadow of the vehicle detection and removal is a key link. In this paper, a novel vehicle's shadow detection and removal algorithm is proposed. Firstly, the texture autocorrelation is used to pre-extracted the shadow of the vehicles. Secondly, the statistical discrimination method is used to evaluate the shadow pre-extraction results. Then the integer wavelet transform is used to re-extracted the misjudgment of the shadow area. Finally, the two shadow extraction results are combined to implement the shadow detection and removal of the vehicle. Experimental results are showed that: the method not only can accurately detect the shadow of the vehicle which is a large difference in grayscale to compare with the background, but also can better detect the shadow of the vehicle which is similar to the background in grayscale. Therefore the method solves the common false detection question of the shadow when use the single method to detect the shadow and remove it, and obtain a perfect shadow detection and removal results.

A Review of Vision-Laser-Based Civil Infrastructure Inspection and Monitoring

“…Compared with rain removal and fog removal, more studies were conducted on solving shadow occlusion. Jianyong et al [ 139 ] developed a vehicle shadow removal method based on texture autocorrelation and integer wavelet transform. Finlayson et al [ 140 ] presented a shadow removal method based on entropy minimization to determine the invariant direction.…”