Performance analysis of robust road sign identification

This study describes performance analysis of a robust system for road sign identification that incorporated two stages of different algorithms. The proposed algorithms consist of HSV color filtering and PCA techniques respectively in detection and recognition stages. The proposed algorithms are able...

Full description

Bibliographic Details
Main Authors:	Ali, Nursabillilah M, Mohd Mustafah, Yasir, Alang Md Rashid, Nahrul Khair
Format:	Article
Language:	English
Published:	IOP Publishing 2013
Subjects:	T Technology (General)
Online Access:	http://irep.iium.edu.my/35997/ http://irep.iium.edu.my/35997/ http://irep.iium.edu.my/35997/1/7._Performance_analysis_of_robust_road_sign_identification.pdf

id	iium-35997
recordtype	eprints
spelling	iium-359972014-03-11T01:30:20Z http://irep.iium.edu.my/35997/ Performance analysis of robust road sign identification Ali, Nursabillilah M Mohd Mustafah, Yasir Alang Md Rashid, Nahrul Khair T Technology (General) This study describes performance analysis of a robust system for road sign identification that incorporated two stages of different algorithms. The proposed algorithms consist of HSV color filtering and PCA techniques respectively in detection and recognition stages. The proposed algorithms are able to detect the three standard types of colored images namely Red, Yellow and Blue. The hypothesis of the study is that road sign images can be used to detect and identify signs that are involved with the existence of occlusions and rotational changes. PCA is known as feature extraction technique that reduces dimensional size. The sign image can be easily recognized and identified by the PCA method as is has been used in many application areas. Based on the experimental result, it shows that the HSV is robust in road sign detection with minimum of 88 and 77 successful rate for non-partial and partial occlusions images. For successful recognition rates using PCA can be achieved in the range of 94-98. The occurrences of all classes are recognized successfully is between 5 and 10 level of occlusions. IOP Publishing 2013 Article PeerReviewed application/pdf en http://irep.iium.edu.my/35997/1/7._Performance_analysis_of_robust_road_sign_identification.pdf Ali, Nursabillilah M and Mohd Mustafah, Yasir and Alang Md Rashid, Nahrul Khair (2013) Performance analysis of robust road sign identification. IOP Conference Series: Materials Science and Engineering, 53 (1). 012017. ISSN 1757-8981 http://stacks.iop.org/1757-899X/53/i=1/a=012017
repository_type	Digital Repository
institution_category	Local University
institution	International Islamic University Malaysia
building	IIUM Repository
collection	Online Access
language	English
topic	T Technology (General)
spellingShingle	T Technology (General) Ali, Nursabillilah M Mohd Mustafah, Yasir Alang Md Rashid, Nahrul Khair Performance analysis of robust road sign identification
description	This study describes performance analysis of a robust system for road sign identification that incorporated two stages of different algorithms. The proposed algorithms consist of HSV color filtering and PCA techniques respectively in detection and recognition stages. The proposed algorithms are able to detect the three standard types of colored images namely Red, Yellow and Blue. The hypothesis of the study is that road sign images can be used to detect and identify signs that are involved with the existence of occlusions and rotational changes. PCA is known as feature extraction technique that reduces dimensional size. The sign image can be easily recognized and identified by the PCA method as is has been used in many application areas. Based on the experimental result, it shows that the HSV is robust in road sign detection with minimum of 88 and 77 successful rate for non-partial and partial occlusions images. For successful recognition rates using PCA can be achieved in the range of 94-98. The occurrences of all classes are recognized successfully is between 5 and 10 level of occlusions.
format	Article
author	Ali, Nursabillilah M Mohd Mustafah, Yasir Alang Md Rashid, Nahrul Khair
author_facet	Ali, Nursabillilah M Mohd Mustafah, Yasir Alang Md Rashid, Nahrul Khair
author_sort	Ali, Nursabillilah M
title	Performance analysis of robust road sign identification
title_short	Performance analysis of robust road sign identification
title_full	Performance analysis of robust road sign identification
title_fullStr	Performance analysis of robust road sign identification
title_full_unstemmed	Performance analysis of robust road sign identification
title_sort	performance analysis of robust road sign identification
publisher	IOP Publishing
publishDate	2013
url	http://irep.iium.edu.my/35997/ http://irep.iium.edu.my/35997/ http://irep.iium.edu.my/35997/1/7._Performance_analysis_of_robust_road_sign_identification.pdf
first_indexed	2023-09-18T20:51:32Z
last_indexed	2023-09-18T20:51:32Z
_version_	1777410026999119872

Performance analysis of robust road sign identification

Similar Items