In this paper Performance of Principle Component Analysis and Discrete Cosine Transform methods for feature reduction in face recognition system is compared. In face recognition system, feature extraction is based on wavelet transform and Support Vector Machine classifier for training and recognition is employed. According to experimental results on ORL face dataset the PCA method gives better performance compared to using DCT method.
| Published in |
Journal of Electrical and Electronic Engineering (Volume 3, Issue 2-1)
This article belongs to the Special Issue Research and Practices in Electrical and Electronic Engineering in Developing Countries |
| DOI | 10.11648/j.jeee.s.2015030201.24 |
| Page(s) | 62-65 |
| Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
| Copyright |
Copyright © The Author(s), 2024. Published by Science Publishing Group |
Face Recognition, Wavelet Transform, PCA, DCT
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APA Style
Mozhde Elahi, Mahsa Gharaee. (2015). Performance Comparison for Face Recognition using PCA and DCT. Journal of Electrical and Electronic Engineering, 3(2-1), 62-65. https://doi.org/10.11648/j.jeee.s.2015030201.24
ACS Style
Mozhde Elahi; Mahsa Gharaee. Performance Comparison for Face Recognition using PCA and DCT. J. Electr. Electron. Eng. 2015, 3(2-1), 62-65. doi: 10.11648/j.jeee.s.2015030201.24
AMA Style
Mozhde Elahi, Mahsa Gharaee. Performance Comparison for Face Recognition using PCA and DCT. J Electr Electron Eng. 2015;3(2-1):62-65. doi: 10.11648/j.jeee.s.2015030201.24
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Download@article{10.11648/j.jeee.s.2015030201.24,
author = {Mozhde Elahi and Mahsa Gharaee},
title = {Performance Comparison for Face Recognition using PCA and DCT},
journal = {Journal of Electrical and Electronic Engineering},
volume = {3},
number = {2-1},
pages = {62-65},
doi = {10.11648/j.jeee.s.2015030201.24},
url = {https://doi.org/10.11648/j.jeee.s.2015030201.24},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.jeee.s.2015030201.24},
abstract = {In this paper Performance of Principle Component Analysis and Discrete Cosine Transform methods for feature reduction in face recognition system is compared. In face recognition system, feature extraction is based on wavelet transform and Support Vector Machine classifier for training and recognition is employed. According to experimental results on ORL face dataset the PCA method gives better performance compared to using DCT method.},
year = {2015}
}
TY - JOUR T1 - Performance Comparison for Face Recognition using PCA and DCT AU - Mozhde Elahi AU - Mahsa Gharaee Y1 - 2015/01/27 PY - 2015 N1 - https://doi.org/10.11648/j.jeee.s.2015030201.24 DO - 10.11648/j.jeee.s.2015030201.24 T2 - Journal of Electrical and Electronic Engineering JF - Journal of Electrical and Electronic Engineering JO - Journal of Electrical and Electronic Engineering SP - 62 EP - 65 PB - Science Publishing Group SN - 2329-1605 UR - https://doi.org/10.11648/j.jeee.s.2015030201.24 AB - In this paper Performance of Principle Component Analysis and Discrete Cosine Transform methods for feature reduction in face recognition system is compared. In face recognition system, feature extraction is based on wavelet transform and Support Vector Machine classifier for training and recognition is employed. According to experimental results on ORL face dataset the PCA method gives better performance compared to using DCT method. VL - 3 IS - 2-1 ER -
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