Detection and Recognition of Mixed Traffic for Driver Assistance System

Driver-assistance systems that monitor driver intent, warn drivers or assist in vehicle guidance are all being actively considered. This paper present computer vision system designed for recognizing road boundary and a number of objects of interest including vehicles, pedestrians, motorcycles and bicycles. The system is designed using Hough transform and Kalman filters to improve the accuracy as well as robustness of the road environment recognition. A Kalman filter object can be configured for each physical object for multiple object tracking. To use the Kalman filter, the moving object must be track. The results are then used as the road contextual information for the following procedure, in which, particular objects of interest, including vehicles, pedestrians, motorcycles and bicycles, are recognized by using a multi-class object detector. The results in various typical but challenging scenarios show the effectiveness of the system. Keywords— Computer vision toolbox, Video processing, Hough transform ,Kalman filters ,Region of interest, Object track ,Driver assistance system , Intelligent vehicles.