Fingerprint matching combining the adjacent feature with curvature of ridges

Chongwen Wang*, Gangyi Ding, Zhiwei Zheng

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

Minutiae matching is the most popular approach to fingerprint verification. A novel feature vector for each fingerprint minutia based on the adjacent feature and curvature of ridges had been defined in this paper. These features are used to identify corresponding minutiae between two fingerprint impressions by computing the Euclidean distance between vectors. A novel fingerprint matching algorithm had been developed using both features. A series of experiments conducted on the public data collection, DB3, FVC2002, demonstrates that the proposed method provides the effectiveness and a good trade-off between speed and accuracy.

Original languageEnglish
Title of host publicationProceedings of the 7th World Congress on Intelligent Control and Automation, WCICA'08
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages6811-6816
Number of pages6
ISBN (Print)9781424421145
DOIs
Publication statusPublished - 2008
Event7th World Congress on Intelligent Control and Automation, WCICA'08 - Chongqing, China
Duration: 25 Jun 200827 Jun 2008

Publication series

NameProceedings of the World Congress on Intelligent Control and Automation (WCICA)

Conference

Conference7th World Congress on Intelligent Control and Automation, WCICA'08
Country/TerritoryChina
CityChongqing
Period25/06/0827/06/08

Keywords

  • Adjacent feature
  • Curvature
  • Fingerprint
  • Matching

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