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Comparison of PCA -, MDF -, and RD-LDA - based feature extraction approaches for hand-based personal recognition by Nikola Pavešić; Slobodan Ribarić; Benjamin Grad is a scholarly article available to read on EtoBox.

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, and Regularized-Direct Linear Discriminant Analysis (RD-LDA) -based feature extraction approaches are tested and compared in an experimental personal recognition system. The system is multimodal and bases on features extracted from nine regions of an image of the palmar surface of the hand. For testing purposes 10 gray-scale images of right hand of 184 people were acquired. The experiments have shown that the best results are obtained with the RD-LDA -based features extraction approach (100% correctness for 920 identification tests and EER = 0.01% for 64170 verification tests).

Author

Nikola Pavešić; Slobodan Ribarić; Benjamin Grad

Publisher

ACM Press

Published

2007

Language

EN