Approach to front vehicle detection and tracking based on multiple features
Zhiqiang Liu · Computer Engineering and Applications Journal · 2011
Vehicle detection is the premise of the automotive anti-collision warning.This paper presents a multi-feature-combined approach to improve the robustness of the vehicle detection in real-time.The approach dose not depend on the lane detection for it is based on the grads feature of the shadow which shows the candidate vehicle regions and it eliminates the noises of the corresponding area by the method of differential box counting.Then,the accurate vehicle area can be located by analyzing the information of vehicle’s horizontal edge feature in the candidate vehicle region.Finally,Kalman filters are used to track the candidate vehicle which will be validated by normalized-mutual-information feature.The result of the experiment has shown that the method provides a robust approach,which can effectively detect the front vehicles in complex traffic circumstances in real time.