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자동차의 자기 주행차선 검출을 위한 시각 센싱

Vision Sensing for the Ego-Lane Detection of a Vehicle

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참고문헌

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초록

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 ratherlong 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 imageline scan replaces the edge detection process of existing methods. Automatic thresholding and spatiotemporal filtering procedures arealso 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.

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 ratherlong 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 imageline scan replaces the edge detection process of existing methods. Automatic thresholding and spatiotemporal filtering procedures arealso 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.

참고문헌 (13)

  1. "IEEE Comput. Intell. Mag.", 2016, 46~58, 10.1109[DOI]
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  8. 박수우, "시각 장애인을 위한 비디오 기반 보행거리 측정", 제어.로봇.시스템학회 논문지, 15(2), pp.139~147 (2009), 제어·로봇·시스템학회
  9. S. C. Yi, "A lane detection approach based on intelligent vision", Comput. Electr. Eng., 42, pp.23~29 (2015)[DOI]
  10. W. Phueakjeen, "A study of the edge detection for road lane", Proc. of IEEE Int'l Conf. on Electrical Engineering, 2011, 995~998
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  12. J. Canny, "A computational approach to edge detection", IEEE Trans. Pattern Anal. Mach. Intell., 8(6), pp.679~698 (1986)

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