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17 March 2008 A novel incremental image reduction principal component analysis and its application for face recognition
R. M. Mutelo, W. L. Woo, S. S. Dlay
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Proceedings Volume 6944, Biometric Technology for Human Identification V; 69440B (2008) https://doi.org/10.1117/12.778722
Event: SPIE Defense and Security Symposium, 2008, Orlando, Florida, United States
Abstract
In this paper, a fast incremental image reduction principal component analysis approach (IIRPCA) is developed for image representation and recognition. As opposed to traditional appearance based image techniques, IRPCA computes the principal components of a sequence of image samples directly on the 2D image matrix incrementally without estimating the covariance matrix. Therefore, IRPCA overcomes the limitations such as the computational cost and memory requirements to making it suitable for real time applications. The feasibility of the proposed approach was tested on a recently published large database consisting of over 2000 face images. IIRPCA shows superiority in terms of computational time, storage and comparable recognition accuracy (94.0%) when compared to recent techniques such as 2DPCA (92.0%) and 2D RPCA (94.5%).
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R. M. Mutelo, W. L. Woo, and S. S. Dlay "A novel incremental image reduction principal component analysis and its application for face recognition", Proc. SPIE 6944, Biometric Technology for Human Identification V, 69440B (17 March 2008); https://doi.org/10.1117/12.778722
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KEYWORDS
Principal component analysis
Facial recognition systems
Databases
Matrices
Feature extraction
Statistical analysis
Image resolution
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