Fingerprint Singular Point Detection Based on Modified Poincare Index Method

Abstract

The use of fingerprint for human identity management has been on the rise lately. Reasons adduced for this include its high level of uniqueness, availability, consistency and universality. The task of human identity management based on fingerprint technology involves a number of processes which include enrolment, enhancement, feature and singular points detection and extraction and pattern matching. Detection and extraction of genuine and reliable feature and singular points are paramount for reliable pattern matching. The limitations of some existing fingerprint singular point detection algorithms include inaccurate detection and failure with some fingerprint pattern and poor quality images. In this paper, a modified Poincare Index fingerprint singular point detection algorithm is proposed for resolving these limitations. The results of the experimental study of the new algorithm on Dataset DB1 of FVC2000 standard fingerprint database show that the new algorithm reliably and adequately detected singular points from fingerprints of all patterns and qualities.