DocumentCode :
1931306
Title :
Road Lane Detection Using H-Maxima and Improved Hough Transform
Author :
Ghazali, Kamarul ; Xiao, Rui ; Ma, Jie
Author_Institution :
Vision & Intell. Syst. Res. Group, Univ. Malaysia Pahang, Pekan, Malaysia
fYear :
2012
fDate :
25-27 Sept. 2012
Firstpage :
205
Lastpage :
208
Abstract :
A fast and improved algorithm with the ability to detect unexpected lane changes is aimed in this paper. A short segment of a long curve has relative low curvature which is approximated as a straight line. Based on the characteristics of physical road lane, this paper presents a lane detection technique based on H-MAXIMA transformation and improved Hough Transform algorithm which first defines the region of interest from input image for reducing searching space, divided the image into near field of view and far field of view. In near field of view, Hough transform has been applied to detect lane markers after image noise filtering. The proposed method has been developed using image processing programming language platform and was tested on collected video data. Promising result was obtained with high efficiency of detection.
Keywords :
Hough transforms; approximation theory; image denoising; road accidents; road safety; video signal processing; H-maxima transformation; Hough transform algorithm; curve curvature approximation; far field of view; image division; image noise filtering; image processing programming language platform; input image; lane marker detection; near field of view; physical road lane detection; region of interest; searching space reduction; straight line; unexpected lane change detection; video data collection; Computational modeling; Image color analysis; Image edge detection; Machine vision; Roads; Transforms; H_MAXIMA; Hough Transform; lane markers;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Intelligence, Modelling and Simulation (CIMSiM), 2012 Fourth International Conference on
Conference_Location :
Kuantan
ISSN :
2166-8531
Print_ISBN :
978-1-4673-3113-5
Type :
conf
DOI :
10.1109/CIMSim.2012.31
Filename :
6338076
Link To Document :
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