Human Face Recognition Using GABOR Filter And Different Self Organizing Maps Neural Networks

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 (SOM) in a hierarchical format in conjunction with Gabor Filters and local...

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Bibliographic Details
Main Author: Dr. Tarik Zeyad
Format: Article
Language:English
Published: Al-Khwarizmi College of Engineering – University of Baghdad 2017-12-01
Series:Al-Khawarizmi Engineering Journal
Subjects:
Online Access:http://alkej.uobaghdad.edu.iq/index.php/alkej/article/view/19
Description
Summary: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 (SOM) in a hierarchical format in conjunction with Gabor Filters and local image sampling. Different types of SOM’s were used and a comparison between the results from these SOM’s was given. 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 and a measure of the time differences between the methods is given.
ISSN:1818-1171
2312-0789