Geometric face recognition approach based on neural network
Author
Source
Journal of College of Education for Pure Sciences
Issue
Vol. 2, Issue 3 (30 Aug. 2012)9 p.
Publisher
University of Thi-Qar College of Education for Pure Sciences
Publication Date
2012-08-30
Country of Publication
Iraq
No. of Pages
9
Main Subjects
Information Technology and Computer Science
Topics
Abstract EN
In this paper, we present a technique to recognize a query person whose human face image is given w.r.t.
a specified database.
The main idea of our approach is to use the most important geometric feature positions on the half face image.
We construct vector of measures between chosen essential features points of the face such as eyes, nose, chin, mouth, face boundaries and so on, and then reduced to vector of measures.
The information taken from frontal view images, yet profile view face images are with small rotation degree to different directions.
We used the ANN technique to determine whether or not the query person is recognized.
We applied 64 human face images taken from the ORL database and 160 real human face images concerned some Iraqi persons.
The recognition results show that the recognition rate is 100 % for images taken from both databases.
American Psychological Association (APA)
Hashim, Kazim Mahdi. 2012. Geometric face recognition approach based on neural network. Journal of College of Education for Pure Sciences،Vol. 2, no. 3.
https://search.emarefa.net/detail/BIM-318495
Modern Language Association (MLA)
Hashim, Kazim Mahdi. Geometric face recognition approach based on neural network. Journal of College of Education for Pure Sciences Vol. 2, no. 3 (Aug. 2012).
https://search.emarefa.net/detail/BIM-318495
American Medical Association (AMA)
Hashim, Kazim Mahdi. Geometric face recognition approach based on neural network. Journal of College of Education for Pure Sciences. 2012. Vol. 2, no. 3.
https://search.emarefa.net/detail/BIM-318495
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-318495