Human Face Recognition Using Gabor Filter and Self Organizing Map Neural Network

Abstract

This work implements the face recognition system based on two stages, the first stage is feature extraction stage and the second stage is the classification stage. The feature extraction stage consists of Self-Organizing Maps in a hierarchical format in conjunction with Gabor Filters and local image sampling. The next stage is the classification stage, and consists of self-organizing map neural network; the goal of this stage is to find the similar image to the input image. The proposal method algorithm implemented by using C++ packages, this work is successful classifier for a face database consist of 20 people with six images for each person.