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.
|Number of pages||9|
|Journal||International Journal of Control, Automation and Systems|
|Publication status||Published - 2016 Feb 1|
Bibliographical noteFunding Information:
Recommended by Associate Editor Sung Jin Yoo under the direction of Editor Myotaeg Lim. This research was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (NRF-2010-0012631).
© 2016, Institute of Control, Robotics and Systems and The Korean Institute of Electrical Engineers and Springer-Verlag Berlin Heidelberg.
All Science Journal Classification (ASJC) codes
- Control and Systems Engineering
- Computer Science Applications