doi: 10.7763/IJCTE.2010.V2.225
Human Face Recognition Using Superior Principal Component Analysis (SPCA)
Arjun V. MANE1
,
Ramesh R. MANZA2 ,
Karbhari V KALE1
- 1Department of Computer Science and Information Technology, Dr. Babasaheb Ambedkar Marathwada University, Aurangabad-431 004 (MS) INDIA,.
- 2Department of Computer Science andInformation Technology, Dr. Babasaheb Ambedkar Marathwada University,Aurangabad-431 004 (MS) INDIA,.
Abstract
Principal Component Analysis (PCA) is a statistical technique used for dimension reduction and recognition, & widely used for facial feature extraction and recognition. In this paper a cluster based SPCA face recognition method has been proposed. Experiments based on ORL face database have performed to compare the recognition rate between tradition PCA, Advanced principal component analysis (APCA), & SPCA. It is found that SPCA is giving the best classification result.
Keywords
- Security
- Biometrics
- Face Recognition
- Principal Component Analysis
- Eigenspace
How to Cite
Arjun V. MANE, Ramesh R. MANZA, and Karbhari V KALE, "Human Face Recognition Using Superior Principal Component Analysis (SPCA)," International Journal of Computer Theory and Engineering, vol. 2, no. 5, pp. 688-691, 2010. https://doi.org/10.7763/IJCTE.2010.V2.225
Copyright & License
Copyright © 2010 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).