Title

Performance Evaluation Of Transform Domain Diagonal Principal Component Analysis For Facial Recognition Employing Different Pre-Processing Spatial Domain Approaches

Abstract

Facial recognition using spatial domain Diagonal Principal Component Analysis (DiaPCA) algorithm produces better accuracy compared to the Two Dimensional PCA (2DPCA). Transform Domain - 2DPCA (TD2DPCA) retains the high recognition accuracy of the 2DPCA while considerably reducing storage requirements and computational complexity. In this work, the Transform Domain PCA implementation of the DiaPCA (TDDiaPCA) is presented. All the test results, for noise free and noisy images, consistently confirm the considerable storage and computational savings for different spatial domain pre-processing scenarios while retaining the high recognition rate. The performance is evaluated using ORL, Yale and FERET databases. Sample results are given. © 2012 IEEE.

Publication Date

10-16-2012

Publication Title

Midwest Symposium on Circuits and Systems

Number of Pages

666-669

Document Type

Article; Proceedings Paper

Personal Identifier

scopus

DOI Link

https://doi.org/10.1109/MWSCAS.2012.6292108

Socpus ID

84867327150 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/84867327150

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