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Human identification system based on moment invariant features

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.

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Abstract

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.

Item Type: Conference or Workshop Item (Full Paper)
Additional Information: 5119/27221
Uncontrolled Keywords: Human Identification; Affine Moment Invariants; Video Surveillance Systems
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7800 Electronics. Computer engineering. Computer hardware. Photoelectronic devices > TK7885 Computer engineering
Kulliyyahs/Centres/Divisions/Institutes: Kulliyyah of Engineering > Department of Mechatronics Engineering
Depositing User: Dr Amir Shafie
Date Deposited: 06 Dec 2012 14:21
Last Modified: 29 Jan 2013 15:35
URI: http://irep.iium.edu.my/id/eprint/27221

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