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Pattern Recognition 43 (2010) 579-583
Invariant pattern recognition using contourlets and AdaBoost
G.Y. Chen, Balázs Kégl1, 2, 3
(2010)

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.
1 :  LAL - Laboratoire de l'Accélérateur Linéaire
2 :  INRIA Saclay - Ile de France - TAO
3 :  LRI - Laboratoire de Recherche en Informatique
Informatique/Traitement du signal et de l'image

Physique/Physique/Physique Numérique

Sciences de l'ingénieur/Traitement du signal et de l'image
Palmprint classification – Wavelets – Contourlets – Feature extraction – AdaBoost