Regenerating face images from multi-spectral palm images using multiple fusion methods

Abstract

This paper established a relationship between multi-spectral palm images and a face image based on multiple fusion methods. The first fusion method to be considered is a feature extraction between different multi-spectral palm images, where multi-spectral CASIA database was used. The second fusion method to be considered is a score fusion between two parts of an output face image. Our method suggests that both right and left hands are used, and that each hand aims to produce a significant part of a face image by using a Multi-Layer Perceptron (MLP) network. This will lead to the second fusion part to reconstruct the full-face image, in order to examine its appearance. This topology provided interesting results of Equal Error Rate (EER) equal to 1.99%.