Human identification system based on moment invariant features

Video surveillance is an active research topic in computer vision. Recent research in video surveillance system has shown an increasing focus on creating reliable systems utilizing non-computationally expensive technique for detecting and observing humans’ appearance, movements and activities. I...

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Main Authors: Mohd Ibrahim, Azhar, Shafie, Amir Akramin, Rashid, Muhammad Mahbubur
Format: Conference or Workshop Item
Language:English
Published: 2012
Subjects:
Online Access:http://irep.iium.edu.my/27221/
http://irep.iium.edu.my/27221/
http://irep.iium.edu.my/27221/1/06271183.pdf
id iium-27221
recordtype eprints
spelling iium-272212013-01-29T07:35:16Z http://irep.iium.edu.my/27221/ Human identification system based on moment invariant features Mohd Ibrahim, Azhar Shafie, Amir Akramin Rashid, Muhammad Mahbubur TK7885 Computer engineering Video surveillance is an active research topic in computer vision. Recent research in video surveillance system has shown an increasing focus on creating reliable systems utilizing non-computationally expensive technique for detecting and observing humans’ appearance, movements and activities. In this paper, we present a human identification technique suitable for video surveillance. The technique we propose includes background subtraction, foreground segmentation, feature extraction and classification. First of all, we extract all foreground objects from the background. Then, we perform a morphological reconstruction algorithm to recover the distorted foreground objects. The feature extraction is done using affine moment invariants of full body and head-shoulder of the extracted foreground objects and these were used to identify human. When the partial occlusion occurs, although feature of full body cannot be extracted, still the features of head shoulder can be extracted. Thus, it has a better classification on solving the issue of the loss of property arising from human occluded easily in practical applications. The experiment results show that this method is effective, and it has strong robustness. 2012-07-03 Conference or Workshop Item PeerReviewed application/pdf en http://irep.iium.edu.my/27221/1/06271183.pdf Mohd Ibrahim, Azhar and Shafie, Amir Akramin and Rashid, Muhammad Mahbubur (2012) Human identification system based on moment invariant features. In: International Conference on Computer and Communication Engineering (ICCCE), 2012 , 3-5th July 2012, Kuala lumpur. http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6271183&tag=1
repository_type Digital Repository
institution_category Local University
institution International Islamic University Malaysia
building IIUM Repository
collection Online Access
language English
topic TK7885 Computer engineering
spellingShingle TK7885 Computer engineering
Mohd Ibrahim, Azhar
Shafie, Amir Akramin
Rashid, Muhammad Mahbubur
Human identification system based on moment invariant features
description Video surveillance is an active research topic in computer vision. Recent research in video surveillance system has shown an increasing focus on creating reliable systems utilizing non-computationally expensive technique for detecting and observing humans’ appearance, movements and activities. In this paper, we present a human identification technique suitable for video surveillance. The technique we propose includes background subtraction, foreground segmentation, feature extraction and classification. First of all, we extract all foreground objects from the background. Then, we perform a morphological reconstruction algorithm to recover the distorted foreground objects. The feature extraction is done using affine moment invariants of full body and head-shoulder of the extracted foreground objects and these were used to identify human. When the partial occlusion occurs, although feature of full body cannot be extracted, still the features of head shoulder can be extracted. Thus, it has a better classification on solving the issue of the loss of property arising from human occluded easily in practical applications. The experiment results show that this method is effective, and it has strong robustness.
format Conference or Workshop Item
author Mohd Ibrahim, Azhar
Shafie, Amir Akramin
Rashid, Muhammad Mahbubur
author_facet Mohd Ibrahim, Azhar
Shafie, Amir Akramin
Rashid, Muhammad Mahbubur
author_sort Mohd Ibrahim, Azhar
title Human identification system based on moment invariant features
title_short Human identification system based on moment invariant features
title_full Human identification system based on moment invariant features
title_fullStr Human identification system based on moment invariant features
title_full_unstemmed Human identification system based on moment invariant features
title_sort human identification system based on moment invariant features
publishDate 2012
url http://irep.iium.edu.my/27221/
http://irep.iium.edu.my/27221/
http://irep.iium.edu.my/27221/1/06271183.pdf
first_indexed 2023-09-18T20:40:29Z
last_indexed 2023-09-18T20:40:29Z
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