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http://dx.doi.org/10.9717/kmms.2016.19.6.979

Traversable Region Detection Algorithm using Lane Information and Texture Analysis  

Hwang, Sung Soo (School of Computer Science and Electronic Engineering, Handong Global University)
Kim, Do Hyun (School of Computer Science and Electronic Engineering, Handong Global University)
Publication Information
Journal of Korea Multimedia Society / v.19, no.6, 2016 , pp. 979-989 More about this Journal
Abstract
Traversable region detection is an essential step for advanced driver assistance systems and self-driving car systems, and it has been conducted by detecting lanes from input images. The performance can be unreliable, however, when the light condition is poor or there exist no lanes on the roads. To solve this problem, this paper proposes an algorithm which utilizes the information about the number of lanes and texture analysis. The proposed algorithm first specifies road region candidates by utilizing the number of lanes information. Among road region candidates, the road region is determined as the region in which texture is homogeneous and texture discontinuities occur around its boundaries. Traversable region is finally detected by dividing the estimated road region with the number of lanes information. This paper combines the proposed algorithm with a lane detection-based method to construct a system, and simulation results show that the system detects traversable region even on the road with poor light conditions or no lanes.
Keywords
Traversable Region Detection; Number of Lanes; Texture Analysis; Histogram Matching;
Citations & Related Records
Times Cited By KSCI : 3  (Citation Analysis)
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