A New Hybrid Technique for Face Identification Based on Facial Parts Moments Descriptors

Authors

  • Shaymaa M. Hamandi University of Technology
  • Abdul Monem S. Rahma Computer Science Dept. \ University of Technology
  • Rehab F. Hassan Computer Science Dept. \ University of Technology

DOI:

https://doi.org/10.30684/etj.v39i1B.1903

Abstract

Robust facial feature extraction is an effective and important process for face recognition and identification system. The facial features should be invariant to scaling, translation, illumination and rotation, several feature extraction techniques may be used to increase the recognition accuracy. This paper inspects three-moment invariants techniques and then determines how is influenced by the variation which may happen to the various shapes of the face (globally and locally) Globally means the whole face shapes and locally means face part's shape (right eye, left eye, mouth, and nose). The proposed technique is tested using CARL database images. The proposal method of the new method that collects the robust features of each method is trained by a feed-forward neural network. The result has been improved and achieved an accuracy of 99.29%.

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Author Biographies

Shaymaa M. Hamandi, University of Technology

Shaymaa M. Hamandi

Ph.D. Student

University of Technology

Baghdad

Iraq

Awarded her M.Sc. from Al Nahrain University, Computer science department in 2006.

She worked at Baghdad Governorate as a manager of the information technology department until 2011, programmed a lot of database systems for financial. stock, and human resources departments. Then worked as a programmer in a public governorate library.

Started her Ph.D. studying in 2018 and now she is in the research stage.

Her research interests include image processing, pattern recognition, and biometrics.

Abdul Monem S. Rahma, Computer Science Dept. \ University of Technology

Prof.Abdul Monem S. Rahma

University of Technology

Baghdad Iraq

Awarded his M.Sc. degree from Brunel University and his Ph.D. from Loughborough University of Technology, the UK in 1982 and 1984, respectively. He taught at the University of Baghdad, Department of Computer Science and the Military College of Engineering, Computer Engineering Department from 1986 to 2003, and works as a Professor at the University of Technology Department of Computer Science. He was Deputy Dean in the Department of Computer Science from 2005 to 2013. From 2013 to 2015, he was the Dean of the Department of Computer Science, University of Technology.

He published 160 papers and four books in the field of computer science and supervised 34 Ph.D. and 65 M.Sc. students.

His research interests include computer graphics image processing, biometrics, and computer security.

 

 

 

Rehab F. Hassan, Computer Science Dept. \ University of Technology

Rehab F. Hassan

Asst. Prof.

University of Technology

Baghdad

Iraq

Awarded her M.Sc. and Ph.D. degree from the University of Technology, computer science department in 1995 and 2005, respectively. She taught at the University of Technology, Computer Science department.

She published a lot of papers in the field of computer science and supervised Ph.D. and M.Sc. students.

Her research interests include computer graphics image processing, and computer security.

 

Published

2021-03-25

How to Cite

Hamandi, S. M., Rahma, A. M. S. ., & Hassan, R. F. (2021). A New Hybrid Technique for Face Identification Based on Facial Parts Moments Descriptors. Engineering and Technology Journal, 39(1B), 117-128. https://doi.org/10.30684/etj.v39i1B.1903