Muda, A. K. and Yun-Huoy, C. and Ahmad, S. (2011) A Comparative Study of Feature Extraction Using PCA and LDA for Face Recognition. In: International Conference on Information Assurance and Security 2011, 5 - 8 Dec, 2011, UTeM, Melaka, Malaysia.
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Abstract
Feature extraction is important in face recognition. This paper presents a comparative study of feature extraction using Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) for face recognition. The evaluation parameters for the study are time and accuracy of each method. The experiments were conducted using six datasets of face images with different disturbance. The results showed that LDA is much better than PCA in overall image with various disturbances. While in time taken evaluation, PCA is faster than LDA.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Subjects: | T Technology > T Technology (General) |
| Divisions: | Faculty of Information and Communication Technology > Department of Software Engineeering |
| Depositing User: | Azah Kamilah Muda |
| Date Deposited: | 09 Dec 2011 12:42 |
| Last Modified: | 28 May 2015 02:17 |
| URI: | http://eprints.utem.edu.my/id/eprint/244 |
| Statistic Details: | View Download Statistic |
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