A novel incremental image reduction principal component analysis and its application for face recognition

R. M. Mutelo, W. L. Woo, S. S. Dlay

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

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%).

Original languageEnglish
Title of host publicationBiometric Technology for Human Identification V
PublisherSPIE
Volume6944
ISBN (Print)9780819471352
DOIs
Publication statusPublished - 17 Mar 2008
EventBiometric Technology for Human Identification V - Orlando, FL, United States
Duration: 18 Mar 200819 Mar 2008

Conference

ConferenceBiometric Technology for Human Identification V
CountryUnited States
CityOrlando, FL
Period18/03/0819/03/08

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