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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my.iium.irep.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 REM 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 |
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TK7885 Computer engineering Mohd Ibrahim, Azhar Shafie, Amir Akramin Rashid, Muhammad Mahbubur Human identification system based on moment invariant features |
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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/27221/1/06271183.pdf http://irep.iium.edu.my/27221/ http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6271183&tag=1 |
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1643609295943630848 |
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13.18916 |