Palmprint recognition using wavelet and support vector machines

Authors:
Xinhong Zhou;Yuhua Peng;Ming Yang
Affiliations:
School of Information Science and Engineering, Shandong University, Jinan, Shandong, People's Republic of China;School of Information Science and Engineering, Shandong University, Jinan, Shandong, People's Republic of China;School of Information Science and Engineering, Shandong University, Jinan, Shandong, People's Republic of China
Venue:
PRICAI'06 Proceedings of the 9th Pacific Rim international conference on Artificial intelligence
Year:
2006

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Abstract

In recent years, palmprint identification has been developed for security purpose. In this paper, a novel scheme of palmprint identification is proposed. We apply 2-dimensional 2_band (Discrete Wavelet Transform) and 3_band wavelet decomposition to get the low subband images, and then use them as identification feature vectors. We choose support vector machines as classifier. The experimental results demonstrate that it is a simple and accurate identification strategy and the correct recognition rate is high up to 100%.