Object recognition improvement in coarse weather condition for automated driving systems

Abstract

For object recognition using camera-captured images, coarse weather condition such as fog / rain causes edge degradation of the target object and adversely affects the detection accuracy. Aiming at constructing a “Minimal Risk Maneuver: MRM” for automated driving systems, we examined applying an algorithm based on "Dark Channel Prior" to improve the identification accuracy. Experimental results with the algorithm depicted the feasibility of the algorithm in terms of our aim. Further development with relevant techniques would be also discussed.