Real time vehicle detection for rear and forward collision warning systems

Abstract

Vehicle detection module is an important application within most of the driver assistance systems. This paper presents a real-time vision based method for detecting vehicles in both rear and forward collision warning systems. The system setup consists of a pair of cameras mounted on each lateral mirror for monitoring rear collisions, whereas camera for forward monitoring is placed on the dashboard. The proposed algorithm selects ROI based on the road lane marking. Two separate modules are functional, one for detecting vehicles in the forward path and other for passing-by vehicles. Profiling and edge detection techniques are used to localize forward path objects. The passing vehicles are detected by temporal differencing. The detected vehicles are tracked in the subsequent frames using mean-shift based tracking. Experiments performed on different road scenarios shows that the proposed method is robust and has a real-time performance. © 2011 Springer-Verlag.