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Conference Paper Robust Lane Detection for Video-Based Navigation Systems
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Authors
Sung Hoon Kim, Jeong-Ho Park, Seong Ik Cho, Soon Young Park, Ki Sung Lee, Kyoung Ho Choi
Issue Date
2007-10
Citation
International Conference on Tools with Artificial Intelligence (ICTAI) 2007, pp.535-538
Language
English
Type
Conference Paper
DOI
https://dx.doi.org/10.1109/ICTAI.2007.20
Project Code
07MD1900, Technology Development for Construction and Management of Tangible Content for Telematics Services, Cho Seong Ik
Abstract
Lane detection from a live video captured in a moving vehicle is an important issue for autonomous vehicles and video-based navigation systems. In this paper, we present a novel idea for robust lane detection and lane color recognition. More specifically, a framework for robust lane detection is presented. Then, a novel idea to reduce illumination effects is presented. Lastly, SVM approach is presented to recognize lane color robustly for various lighting conditions including shadow, backlight, sunset, and so on. By combining information from navigation database, it is possible to decide if we are in the leftmost, middle, or the rightmost lane, which allows us to provide more realistic navigation information to drivers. Simulation results are provided to show the robustness of the proposed idea. © 2007 IEEE.
KSP Keywords
Autonomous vehicle, Color Recognition, Combining information, Lane Detection, Lighting conditions, Moving Vehicle, Navigation database, Navigation information, Rightmost lane, live video, navigation system