Performance Study of LDA and KFA for Gabor Based Face Recognition System

AbstractFace Recognition (FR) has consistently been one of the most formidable problems in Pattern Recognition and many diverse techniques have been proposed over the past few years to enhance its effectiveness. Feature extractors play an instrumental role in establishing recognition accuracy of FR systems and hence in this paper, we ardently focus our attention on the popular Gabor Filter feature extraction technique and comprehensively compare its linear variant, Gabor-LDA with its nonlinear counterpart, Gabor-KLDA to ascertain which technique is better suited for FR tasks. The findings proffered by this work, along with our other studies, form a series intended to aid developers in making informed decisions while building proficient FR systems