Multifractal characteristics of palmprint and its extracted algorithm

Abstract

The palmprint is one of the most reliable physiological characteristics that can be used to distinguish between individuals. In this paper, we propose a palmprint recognition method based on multifractal spectrum technology using statistical moment approaches. The multifractal spectrum of palmprint is calculated by developing an algorithm for extracting palmprint characteristics. The three parameters proposed as the distinguishing palmprint features include the width spread and maximum of multifractal spectrum, and a parameter which describes the asymmetry of the spectrum curve. The identification process can be divided into the following main steps: (1) capturing palmprint image, extracting and normalizing the subimages; (2) defining a coordinate system and calculating partition function; (3) estimating multifractal spectrum; (4) extracting the three parameters and, finally, (5) the feature matching and palmprint identification. The experimental results demonstrate the feasibility of the proposed method.