Gait feature extraction and recognition in biometric system

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Main Authors: Syed Nafis, Syed Ngah Ismail, Muhammad Imran, Ahmad, Said Amiru, l Anwar, Mohd Nazrin, Md Isa, Ruzelita, Ngadiran
Other Authors: m.imran@unimap.edu.my
Format: Article
Language:English
Published: Universiti Teknikal Malaysia Melaka 2019
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Online Access:http://dspace.unimap.edu.my:80/xmlui/handle/123456789/63566
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Institution: Universiti Malaysia Perlis
Language: English
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spelling my.unimap-635662019-12-03T04:49:37Z Gait feature extraction and recognition in biometric system Syed Nafis, Syed Ngah Ismail Muhammad Imran, Ahmad Said Amiru, l Anwar Mohd Nazrin, Md Isa Ruzelita, Ngadiran m.imran@unimap.edu.my Biometric Gait recognition Information fusion Link to publisher's homepage at http://journal.utem.edu.my This research focus on the development an automatic human identification system using gait sequence images. Human identification is widely used in computer vision applications such as surveillance system, criminal investigations and human-computer interaction. Gait sequence image is a nonstationary data and can be modelled using a statistical learning technique. The propose technique consists of three different stages. The pre-processing stage computes the average silhouette images to capture the important information and get a better representation for gait silhouette data. Then a principle component analysis (PCA) technique is applied on the average silhouette to extract the important gait features and reduce a dimension of gait data. A linear projection method used in this stage is able to reduce redundant features and remove noise data from the gait image. Furthermore, this approach will increase a discrimination power in the feature space when dealing with low frequency information. Low dimensional feature distribution in the feature space is assumed Gaussian, thus the Euclidean distance classifier can be used in the classification stage. The propose algorithm is a model-free based which uses gait silhouette features for the compact gait image representation and a linear feature reduction technique to remove redundant and noise information. The proposed algorithm has been tested using a benchmark CASIA datasets. The experimental results show that the best recognition rate is 90% 2019-12-03T04:49:37Z 2019-12-03T04:49:37Z 2016 Article Journal of Telecommunication, Electronic and Computer Engineering, vol.8(4), 2016, 127-132. 2180–1843 2289-8131 (online) http://dspace.unimap.edu.my:80/xmlui/handle/123456789/63566 journal.utem.edu.my/index.php/jtec/article/view/1187 en Universiti Teknikal Malaysia Melaka
institution Universiti Malaysia Perlis
building UniMAP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Perlis
content_source UniMAP Library Digital Repository
url_provider http://dspace.unimap.edu.my/
language English
topic Biometric
Gait recognition
Information fusion
spellingShingle Biometric
Gait recognition
Information fusion
Syed Nafis, Syed Ngah Ismail
Muhammad Imran, Ahmad
Said Amiru, l Anwar
Mohd Nazrin, Md Isa
Ruzelita, Ngadiran
Gait feature extraction and recognition in biometric system
description Link to publisher's homepage at http://journal.utem.edu.my
author2 m.imran@unimap.edu.my
author_facet m.imran@unimap.edu.my
Syed Nafis, Syed Ngah Ismail
Muhammad Imran, Ahmad
Said Amiru, l Anwar
Mohd Nazrin, Md Isa
Ruzelita, Ngadiran
format Article
author Syed Nafis, Syed Ngah Ismail
Muhammad Imran, Ahmad
Said Amiru, l Anwar
Mohd Nazrin, Md Isa
Ruzelita, Ngadiran
author_sort Syed Nafis, Syed Ngah Ismail
title Gait feature extraction and recognition in biometric system
title_short Gait feature extraction and recognition in biometric system
title_full Gait feature extraction and recognition in biometric system
title_fullStr Gait feature extraction and recognition in biometric system
title_full_unstemmed Gait feature extraction and recognition in biometric system
title_sort gait feature extraction and recognition in biometric system
publisher Universiti Teknikal Malaysia Melaka
publishDate 2019
url http://dspace.unimap.edu.my:80/xmlui/handle/123456789/63566
_version_ 1654961443592732672