Online Training for Face Recognition System Using Improved PCA

The variation in illumination is one of the main challenging problem for face recognition. It has been proven that in face recognition, differences caused by illumination variations are more significant than differences between individuals. Recognizing face reliably across changes in pose and illumi...

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Main Author: Widodo Budiharto
Format: Article
Language:English
Published: Bina Nusantara University 2011-12-01
Series:ComTech
Subjects:
Online Access:https://journal.binus.ac.id/index.php/comtech/article/view/2952
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author Widodo Budiharto
author_facet Widodo Budiharto
author_sort Widodo Budiharto
collection DOAJ
description The variation in illumination is one of the main challenging problem for face recognition. It has been proven that in face recognition, differences caused by illumination variations are more significant than differences between individuals. Recognizing face reliably across changes in pose and illumination using PCA has proved to be a much harder problem because eigenfaces method comparing the intensity of the pixel. To solve this problem, this research proposes an online face recognition system using improved PCA for a service robot in indoor environment based on stereo vision. Tested images are improved by generating random values for varying the intensity of face images. A program for online training is also developed where the tested images are captured real-time from camera. Varying illumination in tested images will increase the accuracy using ITS face database which its accuracy is 95.5 %, higher than ATT face database’s as 95.4% and Indian face database’s as 72%. The results from this experiment are still evaluated to be improved in the future.
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spelling doaj.art-d9e80e650f8c4d53aaaf5e50e56970a42023-08-02T04:13:26ZengBina Nusantara UniversityComTech2087-12442476-907X2011-12-01221303131010.21512/comtech.v2i2.29522339Online Training for Face Recognition System Using Improved PCAWidodo Budiharto0Bina Nusantara UniversityThe variation in illumination is one of the main challenging problem for face recognition. It has been proven that in face recognition, differences caused by illumination variations are more significant than differences between individuals. Recognizing face reliably across changes in pose and illumination using PCA has proved to be a much harder problem because eigenfaces method comparing the intensity of the pixel. To solve this problem, this research proposes an online face recognition system using improved PCA for a service robot in indoor environment based on stereo vision. Tested images are improved by generating random values for varying the intensity of face images. A program for online training is also developed where the tested images are captured real-time from camera. Varying illumination in tested images will increase the accuracy using ITS face database which its accuracy is 95.5 %, higher than ATT face database’s as 95.4% and Indian face database’s as 72%. The results from this experiment are still evaluated to be improved in the future.https://journal.binus.ac.id/index.php/comtech/article/view/2952face recognition, illumination, improved PCA, service robot, ITS face database
spellingShingle Widodo Budiharto
Online Training for Face Recognition System Using Improved PCA
ComTech
face recognition, illumination, improved PCA, service robot, ITS face database
title Online Training for Face Recognition System Using Improved PCA
title_full Online Training for Face Recognition System Using Improved PCA
title_fullStr Online Training for Face Recognition System Using Improved PCA
title_full_unstemmed Online Training for Face Recognition System Using Improved PCA
title_short Online Training for Face Recognition System Using Improved PCA
title_sort online training for face recognition system using improved pca
topic face recognition, illumination, improved PCA, service robot, ITS face database
url https://journal.binus.ac.id/index.php/comtech/article/view/2952
work_keys_str_mv AT widodobudiharto onlinetrainingforfacerecognitionsystemusingimprovedpca