A Comparative Study of Feature Extraction Using PCA and LDA for Face Recognition
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....
| Main Authors: | , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2011
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| Subjects: | |
| Online Access: | http://eprints.utem.edu.my/id/eprint/244/ http://eprints.utem.edu.my/id/eprint/244/1/P140.pdf |
| _version_ | 1848886912889126912 |
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| author | Muda, A. K. Yun-Huoy, C. Ahmad, S. |
| author_facet | Muda, A. K. Yun-Huoy, C. Ahmad, S. |
| author_sort | Muda, A. K. |
| building | UTeM Institutional Repository |
| collection | Online Access |
| description | 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. |
| first_indexed | 2025-11-15T19:46:02Z |
| format | Conference or Workshop Item |
| id | utem-244 |
| institution | Universiti Teknikal Malaysia Melaka |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T19:46:02Z |
| publishDate | 2011 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | utem-2442015-05-28T02:17:26Z http://eprints.utem.edu.my/id/eprint/244/ A Comparative Study of Feature Extraction Using PCA and LDA for Face Recognition Muda, A. K. Yun-Huoy, C. Ahmad, S. T Technology (General) 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. 2011 Conference or Workshop Item NonPeerReviewed application/pdf en http://eprints.utem.edu.my/id/eprint/244/1/P140.pdf 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. |
| spellingShingle | T Technology (General) Muda, A. K. Yun-Huoy, C. Ahmad, S. A Comparative Study of Feature Extraction Using PCA and LDA for Face Recognition |
| title | A Comparative Study of Feature Extraction Using PCA and LDA
for Face Recognition |
| title_full | A Comparative Study of Feature Extraction Using PCA and LDA
for Face Recognition |
| title_fullStr | A Comparative Study of Feature Extraction Using PCA and LDA
for Face Recognition |
| title_full_unstemmed | A Comparative Study of Feature Extraction Using PCA and LDA
for Face Recognition |
| title_short | A Comparative Study of Feature Extraction Using PCA and LDA
for Face Recognition |
| title_sort | comparative study of feature extraction using pca and lda
for face recognition |
| topic | T Technology (General) |
| url | http://eprints.utem.edu.my/id/eprint/244/ http://eprints.utem.edu.my/id/eprint/244/1/P140.pdf |