Road lane tracking based on monocular vision

Lane tracking and detection is a complex problem due to the versatility of road conditions in which the road stream of images is analyzed. In this paper, an algorithm was developed to obtain a robust real-time lane tracking under a sudden appearance of obstacles such as vehicles and shadows. The met...

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Main Authors: Al-Amoodi, Abdullah, Balfaqih, Omar, Htike@Muhammad Yusof, Zaw Zaw
Format: Article
Language:English
English
Published: Research India Publications 2015
Subjects:
Online Access:http://irep.iium.edu.my/43041/
http://irep.iium.edu.my/43041/
http://irep.iium.edu.my/43041/1/Lane_tracking.pdf
http://irep.iium.edu.my/43041/4/43041_Road%20lane%20tracking%20based%20on%20monocular%20vision_SCOPUS.pdf
id iium-43041
recordtype eprints
spelling iium-430412017-11-07T08:07:24Z http://irep.iium.edu.my/43041/ Road lane tracking based on monocular vision Al-Amoodi, Abdullah Balfaqih, Omar Htike@Muhammad Yusof, Zaw Zaw AI Indexes (General) Lane tracking and detection is a complex problem due to the versatility of road conditions in which the road stream of images is analyzed. In this paper, an algorithm was developed to obtain a robust real-time lane tracking under a sudden appearance of obstacles such as vehicles and shadows. The method starts with applying Gaussian filter to grey scale images. Then, ROI is defined by finding the lowest mean of all rows in the image. Canny edge detector followed by Hough Transform are applied to the ROI to acquire lines. The information of lines in a sequence of frames are stored to predict the lane position. This method was tested on 1700 frames in different situations and proved its robustness. Research India Publications 2015 Article PeerReviewed application/pdf en http://irep.iium.edu.my/43041/1/Lane_tracking.pdf application/pdf en http://irep.iium.edu.my/43041/4/43041_Road%20lane%20tracking%20based%20on%20monocular%20vision_SCOPUS.pdf Al-Amoodi, Abdullah and Balfaqih, Omar and Htike@Muhammad Yusof, Zaw Zaw (2015) Road lane tracking based on monocular vision. International Journal of Applied Engineering Research, 10 (8). pp. 19647-19658. ISSN 0973-4562 http://www.ripublication.com
repository_type Digital Repository
institution_category Local University
institution International Islamic University Malaysia
building IIUM Repository
collection Online Access
language English
English
topic AI Indexes (General)
spellingShingle AI Indexes (General)
Al-Amoodi, Abdullah
Balfaqih, Omar
Htike@Muhammad Yusof, Zaw Zaw
Road lane tracking based on monocular vision
description Lane tracking and detection is a complex problem due to the versatility of road conditions in which the road stream of images is analyzed. In this paper, an algorithm was developed to obtain a robust real-time lane tracking under a sudden appearance of obstacles such as vehicles and shadows. The method starts with applying Gaussian filter to grey scale images. Then, ROI is defined by finding the lowest mean of all rows in the image. Canny edge detector followed by Hough Transform are applied to the ROI to acquire lines. The information of lines in a sequence of frames are stored to predict the lane position. This method was tested on 1700 frames in different situations and proved its robustness.
format Article
author Al-Amoodi, Abdullah
Balfaqih, Omar
Htike@Muhammad Yusof, Zaw Zaw
author_facet Al-Amoodi, Abdullah
Balfaqih, Omar
Htike@Muhammad Yusof, Zaw Zaw
author_sort Al-Amoodi, Abdullah
title Road lane tracking based on monocular vision
title_short Road lane tracking based on monocular vision
title_full Road lane tracking based on monocular vision
title_fullStr Road lane tracking based on monocular vision
title_full_unstemmed Road lane tracking based on monocular vision
title_sort road lane tracking based on monocular vision
publisher Research India Publications
publishDate 2015
url http://irep.iium.edu.my/43041/
http://irep.iium.edu.my/43041/
http://irep.iium.edu.my/43041/1/Lane_tracking.pdf
http://irep.iium.edu.my/43041/4/43041_Road%20lane%20tracking%20based%20on%20monocular%20vision_SCOPUS.pdf
first_indexed 2023-09-18T21:01:18Z
last_indexed 2023-09-18T21:01:18Z
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