Mono-camera based vehicle detection using effective candidate generation

This paper proposes a novel on-road vehicle detection algorithm for Advanced Driver Assistance Systems. The proposed algorithm uses shadow and edge information of original image to generate the candidate vehicles. The proposed algorithm extracts the shadow region darker than the road, and creates an edge image using the Canny edge detector. It performs AND operation between the shadow image and the edge image. The candidate vehicles are verified by SVM classifier based on the HOG feature vector. The experimental results show that the proposed algorithm provides fast and accurate vehicle detection. And the number of candidates is reasonable for the vehicle verification.