Palmprint identification using feature-level fusion

13 years 4 months ago

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In this paper, we propose a feature-level fusion approach for improving the efficiency of palmprint identification. Multiple elliptical Gabor filters with different orientations are employed to extract the phase information on a palmprint image, which is then merged according to a fusion rule to produce a single feature called the Fusion Code. The similarity of two Fusion Codes is measured by their normalized hamming distance. A dynamic threshold is used for the final decisions. A database containing 9599 palmprint images from 488 different palms is used to validate the performance of the proposed method. Comparing our previous non-fusion approach and the proposed method, improvement in verification and identification are ensured. 2005 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.

Adams Wai-Kin Kong, David Zhang, Mohamed Kamel

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