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Multi-spectral hybrid invariant moments fusion technique for face identification
Joint Authors
Hasan, Rehab F.
Hamandi, Shayma M.
Rahmah, Abd al-Munim Salih
Source
The International Arab Journal of Information Technology
Issue
Vol. 18, Issue 3A (s) (31 May. 2021), pp.405-413, 9 p.
Publisher
Zarqa University Deanship of Scientific Research
Publication Date
2021-05-31
Country of Publication
Jordan
No. of Pages
9
Main Subjects
Information Technology and Computer Science
Abstract EN
For reliable face identification, the fusion process of multi-spectral vision features produces robust classification systems, this paper exploits the power of thermal facial image invariant moments features fused with the visible facial image invariant moments features to propose a new multi-spectral hybrid invariant moment fusion system for face identification.
And employs Feed-forward neural network to train the moments' features and make decisions.
The evaluation system uses databases of visible thermal pairs face images CARL and UTK-IRIS databases and gives an accuracy reaches 99%.
American Psychological Association (APA)
Hamandi, Shayma M.& Rahmah, Abd al-Munim Salih& Hasan, Rehab F.. 2021. Multi-spectral hybrid invariant moments fusion technique for face identification. The International Arab Journal of Information Technology،Vol. 18, no. 3A (s), pp.405-413.
https://search.emarefa.net/detail/BIM-1439892
Modern Language Association (MLA)
Hamandi, Shayma M.…[et al.]. Multi-spectral hybrid invariant moments fusion technique for face identification. The International Arab Journal of Information Technology Vol. 18, no. 3A (Special issue) (2021), pp.405-413.
https://search.emarefa.net/detail/BIM-1439892
American Medical Association (AMA)
Hamandi, Shayma M.& Rahmah, Abd al-Munim Salih& Hasan, Rehab F.. Multi-spectral hybrid invariant moments fusion technique for face identification. The International Arab Journal of Information Technology. 2021. Vol. 18, no. 3A (s), pp.405-413.
https://search.emarefa.net/detail/BIM-1439892
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 411-412
Record ID
BIM-1439892