Adaptive background modeling for dynamics background

An increasing number of CCTV have been deployed in public and crime-prone areas as demand for automatic monitoring system is increasing to counterbalance the limitation of human monitoring. To have a good monitoring system in such places, a good background model is needed in order to reduce amount o...

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Main Authors:	Zainuddin, Nor Afiqah, Mohd Mustafah, Yasir, Shafie, Amir Akramin, Azman, Amelia Wong, Rashidan, Mohd. Ariff, A. Aziz, Nor Nadirah
Format:	Article
Language:	English English
Published:	International Institute for General Systems Studies 2016
Subjects:	T Technology (General)
Online Access:	http://irep.iium.edu.my/53264/ http://irep.iium.edu.my/53264/ http://irep.iium.edu.my/53264/1/53264_Adaptive%20background%20modeling.pdf http://irep.iium.edu.my/53264/2/53264_Adaptive%20background%20modeling_SCOPUS.pdf

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recordtype	eprints
spelling	iium-532642018-01-11T01:36:11Z http://irep.iium.edu.my/53264/ Adaptive background modeling for dynamics background Zainuddin, Nor Afiqah Mohd Mustafah, Yasir Shafie, Amir Akramin Azman, Amelia Wong Rashidan, Mohd. Ariff A. Aziz, Nor Nadirah T Technology (General) An increasing number of CCTV have been deployed in public and crime-prone areas as demand for automatic monitoring system is increasing to counterbalance the limitation of human monitoring. To have a good monitoring system in such places, a good background model is needed in order to reduce amount of the video processing needed for tracking, classification, counting and etc. This paper proposes an adaptive background modeling that is able to model a scene under review at real-time. The proposed modeling system is also expected to be able to handle dynamic backgrounds and common problems in detection methods. A novel patch-based background reconstruction based on highest frequency of occurrences assumption and past pixel observation is proposed. Contrast adjusting method is used to reduce the problem of incorrectly classified foreground which is shadow problem. The proposed algorithm is focused to be tested and analytically compared with the dynamic background at the indoor and outdoor environment. The main challenges of background subtraction such as illumination changes, geometrical changes, stationary moving object problem and high speed object problem are taken care of and extensively discussed in this paper. The experimental results show that the algorithm is able to reconstruct a background model and produce accurate and precise foreground that can be used for other processing stages. International Institute for General Systems Studies 2016 Article PeerReviewed application/pdf en http://irep.iium.edu.my/53264/1/53264_Adaptive%20background%20modeling.pdf application/pdf en http://irep.iium.edu.my/53264/2/53264_Adaptive%20background%20modeling_SCOPUS.pdf Zainuddin, Nor Afiqah and Mohd Mustafah, Yasir and Shafie, Amir Akramin and Azman, Amelia Wong and Rashidan, Mohd. Ariff and A. Aziz, Nor Nadirah (2016) Adaptive background modeling for dynamics background. Advances in Systems Science and Applications, 16 (2). pp. 54-69. ISSN 1078-6236 http://ijassa.ipu.ru/ojs/ijassa/article/view/350/289
repository_type	Digital Repository
institution_category	Local University
institution	International Islamic University Malaysia
building	IIUM Repository
collection	Online Access
language	English English
topic	T Technology (General)
spellingShingle	T Technology (General) Zainuddin, Nor Afiqah Mohd Mustafah, Yasir Shafie, Amir Akramin Azman, Amelia Wong Rashidan, Mohd. Ariff A. Aziz, Nor Nadirah Adaptive background modeling for dynamics background
description	An increasing number of CCTV have been deployed in public and crime-prone areas as demand for automatic monitoring system is increasing to counterbalance the limitation of human monitoring. To have a good monitoring system in such places, a good background model is needed in order to reduce amount of the video processing needed for tracking, classification, counting and etc. This paper proposes an adaptive background modeling that is able to model a scene under review at real-time. The proposed modeling system is also expected to be able to handle dynamic backgrounds and common problems in detection methods. A novel patch-based background reconstruction based on highest frequency of occurrences assumption and past pixel observation is proposed. Contrast adjusting method is used to reduce the problem of incorrectly classified foreground which is shadow problem. The proposed algorithm is focused to be tested and analytically compared with the dynamic background at the indoor and outdoor environment. The main challenges of background subtraction such as illumination changes, geometrical changes, stationary moving object problem and high speed object problem are taken care of and extensively discussed in this paper. The experimental results show that the algorithm is able to reconstruct a background model and produce accurate and precise foreground that can be used for other processing stages.
format	Article
author	Zainuddin, Nor Afiqah Mohd Mustafah, Yasir Shafie, Amir Akramin Azman, Amelia Wong Rashidan, Mohd. Ariff A. Aziz, Nor Nadirah
author_facet	Zainuddin, Nor Afiqah Mohd Mustafah, Yasir Shafie, Amir Akramin Azman, Amelia Wong Rashidan, Mohd. Ariff A. Aziz, Nor Nadirah
author_sort	Zainuddin, Nor Afiqah
title	Adaptive background modeling for dynamics background
title_short	Adaptive background modeling for dynamics background
title_full	Adaptive background modeling for dynamics background
title_fullStr	Adaptive background modeling for dynamics background
title_full_unstemmed	Adaptive background modeling for dynamics background
title_sort	adaptive background modeling for dynamics background
publisher	International Institute for General Systems Studies
publishDate	2016
url	http://irep.iium.edu.my/53264/ http://irep.iium.edu.my/53264/ http://irep.iium.edu.my/53264/1/53264_Adaptive%20background%20modeling.pdf http://irep.iium.edu.my/53264/2/53264_Adaptive%20background%20modeling_SCOPUS.pdf
first_indexed	2023-09-18T21:15:25Z
last_indexed	2023-09-18T21:15:25Z
_version_	1777411529236283392

Adaptive background modeling for dynamics background

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