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http://dx.doi.org/10.5369/JSST.2019.28.2.94

Vision-sensor-based Drivable Area Detection Technique for Environments with Changes in Road Elevation and Vegetation  

Lee, Sangjae (School of Electronics Engineering, Kyungpook National University)
Hyun, Jongkil (School of Electronics Engineering, Kyungpook National University)
Kwon, Yeon Soo (School of Electronics Engineering, Kyungpook National University)
Shim, Jae Hoon (School of Electronics Engineering, Kyungpook National University)
Moon, Byungin (School of Electronics Engineering, Kyungpook National University)
Publication Information
Journal of Sensor Science and Technology / v.28, no.2, 2019 , pp. 94-100 More about this Journal
Abstract
Drivable area detection is a major task in advanced driver assistance systems. For drivable area detection, several studies have proposed vision-sensor-based approaches. However, conventional drivable area detection methods that use vision sensors are not suitable for environments with changes in road elevation. In addition, if the boundary between the road and vegetation is not clear, judging a vegetation area as a drivable area becomes a problem. Therefore, this study proposes an accurate method of detecting drivable areas in environments in which road elevations change and vegetation exists. Experimental results show that when compared to the conventional method, the proposed method improves the average accuracy and recall of drivable area detection on the KITTI vision benchmark suite by 3.42%p and 8.37%p, respectively. In addition, when the proposed vegetation area removal method is applied, the average accuracy and recall are further improved by 6.43%p and 9.68%p, respectively.
Keywords
Vision sensor; Stereo vision; Advanced driver assistance system; Drivable area detection;
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