Palmprint verification with moments

Abstract

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.