Face Recognition Based on PCA on Wavelet Subband of Average-Half-Face

M.P. Satone and Dr. G.K. Kharate
Volume: 8, No: 3, Page: 483 ~ 494, Year: 2012
10.3745/JIPS.2012.8.3.483
Keywords: Face Recognition, Princ ipal Component Analysis, Subband, Wavelet Transform
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Abstract
Many recent events, such as terrorist attacks, exposed defects in most sophisticated security systems. Therefore, it is necessary to improve security data systems based on the body or behavioral characteristics, often called biometrics. Together with the growing interest in the development of human and computer interface and biometric identification, human face recognition has become an active research area. Face recognition appears to offer several advantages over other biometric methods. Nowadays, Principal Component Analysis (PCA) has been widely adopted for the face recognition algorithm. Yet still, PCA has limitations such as poor discriminatory power and large computational load. This paper proposes a novel algorithm for face recognition using a mid band frequency component of partial information which is used for PCA representation. Because the human face has even symmetry, half of a face is sufficient for face recognition. This partial information saves storage and computation time. In comparison with the traditional use of PCA, the proposed method gives better recognition accuracy and discriminatory power. Furthermore, the proposed method reduces the computational load and storage significantly

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Cite this article
IEEE Style
M.P. Satone and Dr. G.K. Kharate, "Face Recognition Based on PCA on Wavelet Subband of Average-Half-Face," Journal of Information Processing Systems, vol. 8, no. 3, pp. 483~494, 2012. DOI: 10.3745/JIPS.2012.8.3.483.

ACM Style
M.P. Satone and Dr. G.K. Kharate, "Face Recognition Based on PCA on Wavelet Subband of Average-Half-Face," Journal of Information Processing Systems, 8, 3, (2012), 483~494. DOI: 10.3745/JIPS.2012.8.3.483.