A MATLAB-Based Convolutional Neural Network Approach For Face Recognition System

Syazana Itqan, Khalid and Syafeeza, Ahmad Radzi and Norhashimah, Mohd Saad (2016) A MATLAB-Based Convolutional Neural Network Approach For Face Recognition System. Journal Of Bioinformatics And Proteomics Review, 2 (1). pp. 1-5. ISSN 2381-0793

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Abstract

The research on face recognition still continues after several decades since the study of this biometric trait exists. This paper discusses a method on developing a MATLAB-based Convolution Neural Network (CNN) face recognition system with Graphical User Interface (GUI) as the user input. The proposed CNN has the ability to accept new subjects by training the last two layers out of four layers to reduce the neural network training time. The image preprocessing steps were implemented in MATLAB, while the CNN algorithm was implemented in C language (using GCC compiler). The main purpose of this research is to develop a complete system of face recognition. A Graphical User Interface (GUI) in MATLAB links all the steps starting from image preprocessing to face identification process. Evaluation was carried out using the images of 40 subjects from AT & T database and 10 subjects from JAFFE database producing 100% accuracy with less than 1 minute average training time when inserting 1 to 10 new subjects into the system.

Item Type:	Article
Uncontrolled Keywords:	Face recognition; Convolution neural network; MATLAB; Graphical user interface
Subjects:	T Technology > T Technology (General)
Divisions:	Faculty of Electronics and Computer Engineering
Depositing User:	Mohd Hannif Jamaludin
Date Deposited:	10 Oct 2016 00:45
Last Modified:	12 Sep 2021 23:33
URI:	http://eprints.utem.edu.my/id/eprint/17280
Statistic Details:	View Download Statistic

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