Face classification for three major ethnic of Orang Asli using Back Propagation Neural Network / Nor Intan Shafini Nasaruddin

In recent years, face recognition has received much attention due to its benefit in many fields (Hossein et al. 2008). For instances, face recognition is widely used in telecommunication, investigation, entertainment, medical area as well as biometric system (Zhao et al, 2003). Importantly, face rec...

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Main Author:	Nasaruddin, Nor Intan Shafini
Format:	Thesis
Language:	English
Published:	2012
Subjects:	Neural networks (Computer science) Data processing
Online Access:	https://ir.uitm.edu.my/id/eprint/64301/1/64301.PDF
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id	my-uitm-ir.64301
record_format	uketd_dc
spelling	my-uitm-ir.643012023-06-19T04:39:06Z Face classification for three major ethnic of Orang Asli using Back Propagation Neural Network / Nor Intan Shafini Nasaruddin 2012 Nasaruddin, Nor Intan Shafini Neural networks (Computer science). Data processing In recent years, face recognition has received much attention due to its benefit in many fields (Hossein et al. 2008). For instances, face recognition is widely used in telecommunication, investigation, entertainment, medical area as well as biometric system (Zhao et al, 2003). Importantly, face recognition is essential for historical research particularly in mixed races. In order to recognize people, there is no such robust and particular technique for face recognition. This is because face recognition is very challenging and will apply different techniques to different fields and applications. In this paper, there is a method has been used to recognize faces which is by using Backpropagation Neural Network (BPNN). Process of face recognition of Orang Asli faces consists of three steps which are image preprocessing, image extraction and classification. Image preprocessing and image extraction are done by using MATLAB. The image classification prototype is developed by using JAVA programming language which is based on supervised learning algorithm, Backpropagation Neural Network. In the training process, learning rate values is adjusted in order to get better result. After the system training, the testing part for face recognition is conducted. The successful results of the recognition are shown is percentage. This experiment is performed on three major classes of ethnics which are Negrito, Senoi and Proto-Malay. 36 images of each ethnic are captured where each of the ethnic has 12 images respectively. 2012 Thesis https://ir.uitm.edu.my/id/eprint/64301/ https://ir.uitm.edu.my/id/eprint/64301/1/64301.PDF text en public masters Universiti Teknologi Mara (UiTM) Faculty of Computer and Mathematical Sciences Yusof, Fakhrul Hazman (Dr. )
institution	Universiti Teknologi MARA
collection	UiTM Institutional Repository
language	English
advisor	Yusof, Fakhrul Hazman (Dr. )
topic	Neural networks (Computer science) Data processing
spellingShingle	Neural networks (Computer science) Data processing Nasaruddin, Nor Intan Shafini Face classification for three major ethnic of Orang Asli using Back Propagation Neural Network / Nor Intan Shafini Nasaruddin
description	In recent years, face recognition has received much attention due to its benefit in many fields (Hossein et al. 2008). For instances, face recognition is widely used in telecommunication, investigation, entertainment, medical area as well as biometric system (Zhao et al, 2003). Importantly, face recognition is essential for historical research particularly in mixed races. In order to recognize people, there is no such robust and particular technique for face recognition. This is because face recognition is very challenging and will apply different techniques to different fields and applications. In this paper, there is a method has been used to recognize faces which is by using Backpropagation Neural Network (BPNN). Process of face recognition of Orang Asli faces consists of three steps which are image preprocessing, image extraction and classification. Image preprocessing and image extraction are done by using MATLAB. The image classification prototype is developed by using JAVA programming language which is based on supervised learning algorithm, Backpropagation Neural Network. In the training process, learning rate values is adjusted in order to get better result. After the system training, the testing part for face recognition is conducted. The successful results of the recognition are shown is percentage. This experiment is performed on three major classes of ethnics which are Negrito, Senoi and Proto-Malay. 36 images of each ethnic are captured where each of the ethnic has 12 images respectively.
format	Thesis
qualification_level	Master's degree
author	Nasaruddin, Nor Intan Shafini
author_facet	Nasaruddin, Nor Intan Shafini
author_sort	Nasaruddin, Nor Intan Shafini
title	Face classification for three major ethnic of Orang Asli using Back Propagation Neural Network / Nor Intan Shafini Nasaruddin
title_short	Face classification for three major ethnic of Orang Asli using Back Propagation Neural Network / Nor Intan Shafini Nasaruddin
title_full	Face classification for three major ethnic of Orang Asli using Back Propagation Neural Network / Nor Intan Shafini Nasaruddin
title_fullStr	Face classification for three major ethnic of Orang Asli using Back Propagation Neural Network / Nor Intan Shafini Nasaruddin
title_full_unstemmed	Face classification for three major ethnic of Orang Asli using Back Propagation Neural Network / Nor Intan Shafini Nasaruddin
title_sort	face classification for three major ethnic of orang asli using back propagation neural network / nor intan shafini nasaruddin
granting_institution	Universiti Teknologi Mara (UiTM)
granting_department	Faculty of Computer and Mathematical Sciences
publishDate	2012
url	https://ir.uitm.edu.my/id/eprint/64301/1/64301.PDF
_version_	1783735436978421760

Face classification for three major ethnic of Orang Asli using Back Propagation Neural Network / Nor Intan Shafini Nasaruddin

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