Biometrics Identification based Face Image Authentication

Abstract<br /> In recent year biometric technology has received a great attention. One of the newest area in biometric technologies is the automatic face recognition. Face recognition has developed over last decades and still a rapidly growing research area. Although, face recognition systems...

Full description

Bibliographic Details
Main Authors: Israa Khidher, Thamir Abdul Hafidh
Format: Article
Language:Arabic
Published: College of Education for Pure Sciences 2009-09-01
Series:مجلة التربية والعلم
Subjects:
Online Access:https://edusj.mosuljournals.com/article_57761_a3188eaed194f1415306c2296b71909f.pdf
id doaj-2f79946deb384af091f9aa53139a6a48
record_format Article
spelling doaj-2f79946deb384af091f9aa53139a6a482020-11-25T02:44:58ZaraCollege of Education for Pure Sciencesمجلة التربية والعلم1812-125X2664-25302009-09-01223617410.33899/edusj.2009.5776157761Biometrics Identification based Face Image AuthenticationIsraa KhidherThamir Abdul HafidhAbstract<br /> In recent year biometric technology has received a great attention. One of the newest area in biometric technologies is the automatic face recognition. Face recognition has developed over last decades and still a rapidly growing research area. Although, face recognition systems have reached a level of practical success but still remains a challenging problem due to large variation in face images. The aim of the proposed work is to build an efficient automatic face recognition. Data base of gray-level images for the proposed system are selected from the Face Recognition Technology FERET. Then primary processing to these images are performed through the downsampled to each face by bilinear method. Then these images were masked by a rectangle that include face region only. <br /> Wavelets transformation is based for face recognition in this experiment due to their powerful efficiency in face recognition area. Face features were extracted through the use of the 2D 2-level wavelets decomposition. The 2D Vertical and Horizontal subimages are selected. These subimages are selected due to their less sensitivity to image variations. As well as their components form the most informative subimage equipped with the highest discriminating power. Then the images are segmented blocks, the Statistical moment is used to extract features per block. The proposed work used accurate techniques to analysis the recognition which reflects significant enhancement results. These results are represented by accurate measures varied from 75% to more than 100% compared with other system on the same area.https://edusj.mosuljournals.com/article_57761_a3188eaed194f1415306c2296b71909f.pdfwavelets transformationbiometrics identificationface image authenticationface recognition
collection DOAJ
language Arabic
format Article
sources DOAJ
author Israa Khidher
Thamir Abdul Hafidh
spellingShingle Israa Khidher
Thamir Abdul Hafidh
Biometrics Identification based Face Image Authentication
مجلة التربية والعلم
wavelets transformation
biometrics identification
face image authentication
face recognition
author_facet Israa Khidher
Thamir Abdul Hafidh
author_sort Israa Khidher
title Biometrics Identification based Face Image Authentication
title_short Biometrics Identification based Face Image Authentication
title_full Biometrics Identification based Face Image Authentication
title_fullStr Biometrics Identification based Face Image Authentication
title_full_unstemmed Biometrics Identification based Face Image Authentication
title_sort biometrics identification based face image authentication
publisher College of Education for Pure Sciences
series مجلة التربية والعلم
issn 1812-125X
2664-2530
publishDate 2009-09-01
description Abstract<br /> In recent year biometric technology has received a great attention. One of the newest area in biometric technologies is the automatic face recognition. Face recognition has developed over last decades and still a rapidly growing research area. Although, face recognition systems have reached a level of practical success but still remains a challenging problem due to large variation in face images. The aim of the proposed work is to build an efficient automatic face recognition. Data base of gray-level images for the proposed system are selected from the Face Recognition Technology FERET. Then primary processing to these images are performed through the downsampled to each face by bilinear method. Then these images were masked by a rectangle that include face region only. <br /> Wavelets transformation is based for face recognition in this experiment due to their powerful efficiency in face recognition area. Face features were extracted through the use of the 2D 2-level wavelets decomposition. The 2D Vertical and Horizontal subimages are selected. These subimages are selected due to their less sensitivity to image variations. As well as their components form the most informative subimage equipped with the highest discriminating power. Then the images are segmented blocks, the Statistical moment is used to extract features per block. The proposed work used accurate techniques to analysis the recognition which reflects significant enhancement results. These results are represented by accurate measures varied from 75% to more than 100% compared with other system on the same area.
topic wavelets transformation
biometrics identification
face image authentication
face recognition
url https://edusj.mosuljournals.com/article_57761_a3188eaed194f1415306c2296b71909f.pdf
work_keys_str_mv AT israakhidher biometricsidentificationbasedfaceimageauthentication
AT thamirabdulhafidh biometricsidentificationbasedfaceimageauthentication
_version_ 1724764804486266880