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
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