Road lane detection using h-maxima and improved hough transform

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 techn...

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Main Authors: Kamarul Hawari, Ghazali, Xiao, Rui, Ma, Jie
Format: Conference or Workshop Item
Language:English
Published: IEEE 2012
Subjects:
Online Access:http://umpir.ump.edu.my/id/eprint/26738/1/Road%20lane%20detection%20using%20h-maxima%20and%20improved%20hough%20transform.pdf
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author Kamarul Hawari, Ghazali
Xiao, Rui
Ma, Jie
author_facet Kamarul Hawari, Ghazali
Xiao, Rui
Ma, Jie
author_sort Kamarul Hawari, Ghazali
collection UMP
description 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.
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spelling UMPir267382020-02-17T02:05:26Z http://umpir.ump.edu.my/id/eprint/26738/ Road lane detection using h-maxima and improved hough transform Kamarul Hawari, Ghazali Xiao, Rui Ma, Jie TK Electrical engineering. Electronics Nuclear engineering 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. IEEE 2012 Conference or Workshop Item PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/26738/1/Road%20lane%20detection%20using%20h-maxima%20and%20improved%20hough%20transform.pdf Kamarul Hawari, Ghazali and Xiao, Rui and Ma, Jie (2012) Road lane detection using h-maxima and improved hough transform. In: 4th International Conference on Computational Intelligence, Modelling and Simulation (CIMSim 2012) , 25-27 September 2012 , Kuantan, Pahang Darul Makmur. pp. 205-208.. ISSN 2166-8523 https://doi.org/10.1109/CIMSim.2012.31
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Kamarul Hawari, Ghazali
Xiao, Rui
Ma, Jie
Road lane detection using h-maxima and improved hough transform
title Road lane detection using h-maxima and improved hough transform
title_full Road lane detection using h-maxima and improved hough transform
title_fullStr Road lane detection using h-maxima and improved hough transform
title_full_unstemmed Road lane detection using h-maxima and improved hough transform
title_short Road lane detection using h-maxima and improved hough transform
title_sort road lane detection using h maxima and improved hough transform
topic TK Electrical engineering. Electronics Nuclear engineering
url http://umpir.ump.edu.my/id/eprint/26738/1/Road%20lane%20detection%20using%20h-maxima%20and%20improved%20hough%20transform.pdf
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