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http://dx.doi.org/10.5369/JSST.2018.27.2.137

Vision Sensing for the Ego-Lane Detection of a Vehicle  

Kim, Dong-Uk (Department of Electronic Engineering, Graduate School, Daegu University)
Do, Yongtae (School of Electronic & Electrical Engineering, Daegu Unversity)
Publication Information
Journal of Sensor Science and Technology / v.27, no.2, 2018 , pp. 137-141 More about this Journal
Abstract
Detecting the ego-lane of a vehicle (the lane on which the vehicle is currently running) is one of the basic techniques for a smart car. Vision sensing is a widely-used method for the ego-lane detection. Existing studies usually find road lane lines by detecting edge pixels in the image from a vehicle camera, and then connecting the edge pixels using Hough Transform. However, this approach takes rather long processing time, and too many straight lines are often detected resulting in false detections in various road conditions. In this paper, we find the lane lines by scanning only a limited number of horizontal lines within a small image region of interest. The horizontal image line scan replaces the edge detection process of existing methods. Automatic thresholding and spatiotemporal filtering procedures are also proposed in order to make our method reliable. In the experiments using real road images of different conditions, the proposed method resulted in high success rate.
Keywords
Smart car; Vision sensing; Lane detection; Hough Transform;
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Times Cited By KSCI : 2  (Citation Analysis)
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