Face Recognition using Gaborface-based 2DPCA and (2D)2PCA Classification with Ensemble and Multichannel Model

This paper introduces Gaborface-based 2DPCA and (2D)
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PCA classification method based on 2D Gaborface matrices rather than transformed ID feature vectors. Two kinds of strategies to use the bank of Gaborfaces are proposed: ensemble Gaborface representation (EGFR) and multichannel Gaborface representation (MGFR). The feasibility of our method is proved with the experimental results on the ORL and Yale databases. In particular, the MGFR-based (2D)
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PCA method achieves 100% recognition accuracy for ORL database, and 98.89% accuracy for Yale database with five training samples per class