Abstract: Based on the ViBE algorithm and the edge and color characteristics of vehicles in traffic surveillance video, a multi-feature fusion algorithm is proposed to detect and remove vehicle shadows in complex traffic scenes. The method uses ViBE to extract foreground targets, and detects shadow by serial fusion strategy. Firstly, on the basis of the traditional edge-based shadow detection, the level set method is used to achieve rapid filling of inner edges of multiple foreground targets instead of horizontal and vertical operation. After obtaining candidate shadow regions, the HSV color feature and the morphological processing are combined to remove shadow perfectly. Tests with different video image sequences show that the proposed multi-feature fusion algorithm can effectively remove cast shadows and is superior to methods based on a single feature, which is suitable for complex traffic scenes.

Key words: ViBE, edge feature, color feature, multi-feature fusion, level set, HSV, shadow removal