Face Recognition using Sub-Holistic PCA

This paper proposes a face recognition scheme that enhances the correct face recognition rate as compared to conventional Principal Component Analysis (PCA). The proposed scheme, Sub-Holistic PCA (SH-PCA), was tested using ORL database and out performed PCA for all test scenarios. SH-PCA requires mo...

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Bibliographic Details
Main Authors: Khan, M.M., Javed, M.Y., Anjum, M.A.
Format: Conference Proceeding
Language:English
Subjects:
Covariance matrix
Educational institutions
Eigenface[unk]
Eigenvalues
Eigenvalues and eigenfunctions
Face recognition
Histogram Equalization
Holistic
Image databases
Mechanical engineering
PCA
Performance evaluation
Principal component analysis
Surveillance
Testing
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Description
Summary:This paper proposes a face recognition scheme that enhances the correct face recognition rate as compared to conventional Principal Component Analysis (PCA). The proposed scheme, Sub-Holistic PCA (SH-PCA), was tested using ORL database and out performed PCA for all test scenarios. SH-PCA requires more computational power and memory as compared to PCA however it yields an improvement of 6% correct recognition on the complete ORL database of 400 images. The correct recognition rate for the complete ORL database is 90% for the SH-PCA technique.
DOI:10.1109/ICICT.2005.1598573