Multi-Spectral Hybrid Invariant Moments Fusion Technique for Face Identification

Shaymaa Hamandi, Abdul Monem Rahma, and Rehab Hassan

Computer Science Department, University of Technology, Iraq

Abstract: 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%.

Keywords: Feed-forward neural network, affine moments, face recognition, invariant moments, shape descriptor, zernike moments.

Received February 21, 2021; accepted March 7, 2021