Palmprint verification is an approach for verifying a palmprint input by matching the input to the claimed
identity template stored in a database. If the dissimilarity measure between the input and the claimed template is
below the predefined threshold value, the palmprint input is verified possessing same identity as the claimed
identity template. This paper introduces an experimental evaluation of the effectiveness of utilizing three well
known orthogonal moments, namely Zernike moments, pseudo Zernike moments and Legendre moments, in the
application of palmprint verification. Moments are the most commonly used technique in character feature
extraction. The idea of implementing orthogonal moments as palmprint feature extractors is prompted by the fact
that principal features of both character and palmprint are based on line structure. These orthogonal moments are
able to define statistical and geometrical features containing line structure information about palmprint. An
experimental study about verification rate of the palmprint authentication system using these three orthogonal
moments as feature descriptors has been discussed here. Experimental results show that the performance of the
system is dependent on the moment order as well as the type of moments. The orthogonal property of these
moments is able to characterize independent features of the palmprint image and thus have minimum
information redundancy in a moment set. Pseudo Zernike moments of order of 15 has the best performance
among all the moments. Its verification rate is 95.75%, which also represents the overall performance of this
palmprint verification system
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