Pengenalan Citra Wajah Dengan Menggunakan Transformasi Wavelet Diskrit dan Jaringan Saraf Tiruan Back-Propagation

This paper discusses the facial image recognition system using Discrete Wavelet Transform and back-propagation artificial neural network. Discrete Wavelet Transform processes the input image to obtain the essential features found on the face image. These features are then classified using an back-pr...

Full description

Bibliographic Details
Main Author: Suhendry Effendy
Format: Article
Language:English
Published: Bina Nusantara University 2010-12-01
Series:ComTech
Subjects:
Online Access:https://journal.binus.ac.id/index.php/comtech/article/view/2569
id doaj-0df83cf01aad49748ecbe32b98f392c6
record_format Article
spelling doaj-0df83cf01aad49748ecbe32b98f392c62020-11-25T02:55:49ZengBina Nusantara UniversityComTech2087-12442476-907X2010-12-011269170010.21512/comtech.v1i2.25691969Pengenalan Citra Wajah Dengan Menggunakan Transformasi Wavelet Diskrit dan Jaringan Saraf Tiruan Back-PropagationSuhendry Effendy0Bina Nusantara UniversityThis paper discusses the facial image recognition system using Discrete Wavelet Transform and back-propagation artificial neural network. Discrete Wavelet Transform processes the input image to obtain the essential features found on the face image. These features are then classified using an back-propagation artificial neural network for the input image to be identified. Testing the system using facial images in AT & T Database of Faces of 400 images comprising 40 facial images of individuals and web-camera catches as many as 100 images of 10 individuals. The accuracy of level of recognition on AT & T Database of Faces reaches 93.5%, while the accuracy of level of recognition on a web-camera capture images up to 96%. Testing is also done on image of AT & T Database of Faces with given noise. Apparently the noise in the image does not give meaningful effect on the level of recognition accuracy.https://journal.binus.ac.id/index.php/comtech/article/view/2569face recognition, discrete wavelet transformation, artificial neural network, back-propagation
collection DOAJ
language English
format Article
sources DOAJ
author Suhendry Effendy
spellingShingle Suhendry Effendy
Pengenalan Citra Wajah Dengan Menggunakan Transformasi Wavelet Diskrit dan Jaringan Saraf Tiruan Back-Propagation
ComTech
face recognition, discrete wavelet transformation, artificial neural network, back-propagation
author_facet Suhendry Effendy
author_sort Suhendry Effendy
title Pengenalan Citra Wajah Dengan Menggunakan Transformasi Wavelet Diskrit dan Jaringan Saraf Tiruan Back-Propagation
title_short Pengenalan Citra Wajah Dengan Menggunakan Transformasi Wavelet Diskrit dan Jaringan Saraf Tiruan Back-Propagation
title_full Pengenalan Citra Wajah Dengan Menggunakan Transformasi Wavelet Diskrit dan Jaringan Saraf Tiruan Back-Propagation
title_fullStr Pengenalan Citra Wajah Dengan Menggunakan Transformasi Wavelet Diskrit dan Jaringan Saraf Tiruan Back-Propagation
title_full_unstemmed Pengenalan Citra Wajah Dengan Menggunakan Transformasi Wavelet Diskrit dan Jaringan Saraf Tiruan Back-Propagation
title_sort pengenalan citra wajah dengan menggunakan transformasi wavelet diskrit dan jaringan saraf tiruan back-propagation
publisher Bina Nusantara University
series ComTech
issn 2087-1244
2476-907X
publishDate 2010-12-01
description This paper discusses the facial image recognition system using Discrete Wavelet Transform and back-propagation artificial neural network. Discrete Wavelet Transform processes the input image to obtain the essential features found on the face image. These features are then classified using an back-propagation artificial neural network for the input image to be identified. Testing the system using facial images in AT & T Database of Faces of 400 images comprising 40 facial images of individuals and web-camera catches as many as 100 images of 10 individuals. The accuracy of level of recognition on AT & T Database of Faces reaches 93.5%, while the accuracy of level of recognition on a web-camera capture images up to 96%. Testing is also done on image of AT & T Database of Faces with given noise. Apparently the noise in the image does not give meaningful effect on the level of recognition accuracy.
topic face recognition, discrete wavelet transformation, artificial neural network, back-propagation
url https://journal.binus.ac.id/index.php/comtech/article/view/2569
work_keys_str_mv AT suhendryeffendy pengenalancitrawajahdenganmenggunakantransformasiwaveletdiskritdanjaringansaraftiruanbackpropagation
_version_ 1724716077360873472