Randomized approach with geometric constraints to fingerprint verification

Kuo Chin Fan, Cheng Wen Liu, Yuan Kai Wang

Research output: Contribution to journalArticlepeer-review

12 Scopus citations

Abstract

In this paper, a fuzzy bipartite weighted graph model is proposed to solve fingerprint verification problem. A fingerprint image is preprocessed first to form clusters of feature points, which are called feature point clusters. Twenty-four attributes are extracted for each feature point cluster. The attributes are characterized by fuzzy values. Attributes of an input image to be verified are considered as the set of left nodes in a fuzzy bipartite weighted graph, and the attributes of claimed template fingerprint image are considered as the set of right nodes in the graph. The fingerprint verification problem is thus converted into a fuzzy bipartite weighted graph matching problem. A matching algorithm is proposed for the fuzzy bipartite weighted graph model to find an optimal matching with a goodness score. Experimental results reveal the feasibility of the proposed approach in fingerprint verification.

Original languageEnglish
Pages (from-to)1793-1803
Number of pages11
JournalPattern Recognition
Volume33
Issue number11
DOIs
StatePublished - 2000

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