A Blind Spot Detection Warning System based on Gabor Filtering and Optical Flow for E-mirror Applications

Abstract

Blind Spot Detection (BSD) is an important technique for ADAS. We propose a BSD algorithm using Gabor filtering and optical flow to detect vehicles in the blind spot region for both day-time and night-time applications. For the day-time scene, the Gabor filtering is used to detect the vehicles, inside lane line, and outside lane line. After detection, the optical flow information calculated according to Horn-Schunck method is used to judge the motion of the vehicle candidates and filter the mistake-judgement. For the night-time scene, we try to find the head-light of the approaching cars. First, we perform binarization on the image first, find the center of gravity of the light-area, classify the light-area into 2 groups and judge it as a vehicle or not. The proposed BSD system achieves 93.58% recall and 95.83% precision in day time scene and 90.22% recall and 92.76% precision in night time scene. The algorithm can achieve performance of 89 fps on Intel Core I7 and 50 fps on Renesas R-Car M2 under 640x480 resolution.