Title: On impact of PCA for solving classification tasks defined on facial images

Authors: Boris Strandjev; Gennady Agre

Addresses: Musala Soft JSC, Sofia, Bulgaria ' Department Technologies for Knowledge Management and Processing, Institute of Information and Communication Technologies, Bulgarian Academy of Sciences, Acad. G. Bonchev str., 2, 1113 Sofia, Bulgaria

Abstract: The paper presents some experiments investigating the applicability of the principal component analysis method for solving several concept learning tasks defined on images of faces. The results have shown that, in most cases, the applied transformation improves the classification accuracy of used concept learning algorithms. In addition the experiments have confirmed a possible relation between the quality of the obtained improvements and the complexity of the concepts to be learnt. This relation has the potential to be an objective measure of 'concept complexity'.

Keywords: principal component analysis; PCA; classification; facial images; eigenfaces; concept complexity; biometrics; human faces; concept learning; facial recognition.

DOI: 10.1504/IJRIS.2014.066245

International Journal of Reasoning-based Intelligent Systems, 2014 Vol.6 No.3/4, pp.85 - 92

Received: 08 May 2021
Accepted: 12 May 2021

Published online: 09 Dec 2014 *

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