Journal
PATTERN RECOGNITION
Volume 43, Issue 3, Pages 579-583Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.patcog.2009.08.020
Keywords
Palmprint classification; Wavelets; Contourlets; Feature extraction; AdaBoost
Funding
- Natural Sciences and Engineering Research Council of Canada (NSERC)
- Canadian Space Agency Postdoctoral Fellowship
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In this paper, we propose new methods for palmprint classification and handwritten numeral recognition by using the contourlet features. The contourlet transform is a new two dimensional extension of the wavelet transform using multiscale and directional filter banks. It can effectively capture smooth contours that are the dominant features in palmprint images and handwritten numeral images. AdaBoost is used as a classifier in the experiments. Experimental results show that the contourlet features are very stable features for invariant palmprint classification and handwritten numeral recognition, and better classification rates are reported when compared with other existing classification methods. (C) 2009 Elsevier Ltd. All rights reserved.
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