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