earticle

영어

A 2D-video processing technique for automatic detection of incoming vehicles at night light conditions is a challenging task for any Advanced Driver Assistance Systems (ADAS). We present a novel image processing technique to be used by ADAS to detect and track incoming vehicle’s front headlamp for estimating real time velocity under such conditions. To capture the incoming traffic a standard C-MOS camera is mounted in the front panel of the vehicle and pre-processing filters are applied on each frame for removing impulse noise. Headlamp blobs are segmented from the rectified frame using intensity thresholds. Area of the blob is calculated based on the motion data and is used to predict the real time velocity of the vehicle. Optical flow concept is applied to predict Motion in the headlamps and tracked by kalman filtering. Experiments are conducted to estimate the training set parameters of the distance function. Results that demonstrate system’s high velocity prediction rates using the best practices of image processing and optical flow are presented.