Wet area and puddle detection for Advanced Driver Assistance Systems (ADAS) using a stereo camera

Wet area or puddle detection is one of the key issues for safe driving and future Advanced Driver Assistance Systems (ADAS). A new methodology for the detection of wet areas and puddles using a stereo camera is presented in this paper. Because wet areas and puddles have different characteristics, the two areas are separately treated and different detection algorithms are proposed. For the detection of wet areas, color information is used for hypothesis generation (HG) and a support vector machine (SVM) is employed for hypothesis verification (HV). In HV, three features are proposed for classification; these are the polarization difference, graininess and gradient magnitude. For the detection of puddles, the depth map obtained by a stereo camera is used to exploit the fact that abrupt depth changes are detected around the puddles. In the experiment, it is shown that the proposed methods have a robust performance for the detection of wet areas or puddles.