Mobile Face Recognition Application using Eigen face Approaches for Android
Face recognition is one of current biometrics identification methods, that based on the measuring to one of human biological characteristics and utilize them to recognize individuals. these characteristics which are called biometric they are hard to fake because they identify a person by measuring o...
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Al-Mustansiriyah University
2019-08-01
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doaj-6fc42336de96424ebb2efcceb01e79f02020-11-24T21:23:42ZaraAl-Mustansiriyah UniversityMustansiriyah Journal of Science1814-635X2521-35202019-08-0130111912410.23851/mjs.v30i1.540248Mobile Face Recognition Application using Eigen face Approaches for Androidmais mohamed husein0Dhia Alzubaydi1Computer Science Department Mustansiriyah UniversityComputer Science Department Mustansiriyah UniversityFace recognition is one of current biometrics identification methods, that based on the measuring to one of human biological characteristics and utilize them to recognize individuals. these characteristics which are called biometric they are hard to fake because they identify a person by measuring one of its biological characteristics such as (finger print, iris print and face print). With the rapid improvement of mobile technologies that happen in last decade face recognition process can make using mobile phone, this paper explains the building of mobile face recognition system using Eigen face approach, Experimental results have been tested on a local data-set that has been created to analyze the efficiency of the application in various cases including different illumination conditions, variation of view, and orientation, the recognition rate of the application when testing on Galaxy Grand Prime + was 78.4. while The recognition rate when testing on Galaxy Note 5 was 82.4. The accuracy of this application can reach to 100% if we use camera with high accuracy and on good light condition.http://mjs.uomustansiriyah.edu.iq/ojs1/index.php/MJS/article/view/540Eigen face, Cascade classifier. |
collection |
DOAJ |
language |
Arabic |
format |
Article |
sources |
DOAJ |
author |
mais mohamed husein Dhia Alzubaydi |
spellingShingle |
mais mohamed husein Dhia Alzubaydi Mobile Face Recognition Application using Eigen face Approaches for Android Mustansiriyah Journal of Science Eigen face, Cascade classifier. |
author_facet |
mais mohamed husein Dhia Alzubaydi |
author_sort |
mais mohamed husein |
title |
Mobile Face Recognition Application using Eigen face Approaches for Android |
title_short |
Mobile Face Recognition Application using Eigen face Approaches for Android |
title_full |
Mobile Face Recognition Application using Eigen face Approaches for Android |
title_fullStr |
Mobile Face Recognition Application using Eigen face Approaches for Android |
title_full_unstemmed |
Mobile Face Recognition Application using Eigen face Approaches for Android |
title_sort |
mobile face recognition application using eigen face approaches for android |
publisher |
Al-Mustansiriyah University |
series |
Mustansiriyah Journal of Science |
issn |
1814-635X 2521-3520 |
publishDate |
2019-08-01 |
description |
Face recognition is one of current biometrics identification methods, that based on the measuring to one of human biological characteristics and utilize them to recognize individuals. these characteristics which are called biometric they are hard to fake because they identify a person by measuring one of its biological characteristics such as (finger print, iris print and face print). With the rapid improvement of mobile technologies that happen in last decade face recognition process can make using mobile phone, this paper explains the building of mobile face recognition system using Eigen face approach, Experimental results have been tested on a local data-set that has been created to analyze the efficiency of the application in various cases including different illumination conditions, variation of view, and orientation, the recognition rate of the application when testing on Galaxy Grand Prime + was 78.4. while The recognition rate when testing on Galaxy Note 5 was 82.4. The accuracy of this application can reach to 100% if we use camera with high accuracy and on good light condition. |
topic |
Eigen face, Cascade classifier. |
url |
http://mjs.uomustansiriyah.edu.iq/ojs1/index.php/MJS/article/view/540 |
work_keys_str_mv |
AT maismohamedhusein mobilefacerecognitionapplicationusingeigenfaceapproachesforandroid AT dhiaalzubaydi mobilefacerecognitionapplicationusingeigenfaceapproachesforandroid |
_version_ |
1725991547851243520 |