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