A directional approach to fingerprint classification

Document Type

Article

Publication Date

3-1-2008

Abstract

In this article, we present a new fingerprint classification algorithm. Singular points are first extracted from enhanced fingerprint direction images with a resolution of 2 × 2 pixels by the modified SEA algorithm. Based on the number of singular points, fingerprints are categorized into types of "arch", "whorl", and "solitary". Solitary fingerprints are properly rotated and then further processed to generate direction patterns that lead to establishment of individual direction template. Direction constraints are formed and derived from pattern descriptors by their structural layout. Decision rules are then established and pattern templates are classified into three more types: "right loop", "left loop", and "tented arch". NIST-4 database was used for an experimental test, and our classification accuracy was 91.62% with 1.55% rejection on the five-class system (94.38% on the four-class system), which is the best result on the five-class system to-date. An additional experiment on NIST-14 database reports 89.15% accuracy with 3.07% rejection. © 2008 World Scientific Publishing Company.

Identifier

44349127839 (Scopus)

Publication Title

International Journal of Pattern Recognition and Artificial Intelligence

External Full Text Location

https://doi.org/10.1142/S0218001408006211

ISSN

02180014

First Page

347

Last Page

365

Issue

2

Volume

22

Fund Ref

Chung Yuan Christian University

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