Automatic fingerprints image generation using evolutionary algorithm

Ung Keun Cho, Jin Hyuk Hong, Sung Bae Cho

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Constructing a fingerprint database is important to evaluate the performance of an automatic fingerprint recognition system. Because of the difficulty in collecting fingerprint samples, there are only few benchmark databases available. Moreover, various types of fingerprints should be required to get a fair assessment on how robust the system is against various environments. This paper presents a novel method that generates various fingerprint images automatically from only a few training samples by using the genetic algorithm. Fingerprint images generated by the proposed method include similar characteristics of those collected from the corresponding real environment. Experiments with real fingerprints verify the usefulness of the proposed method.

Original languageEnglish
Title of host publicationAdvances in Biometrics - International Conference, ICB 2007, Proceedings
PublisherSpringer Verlag
Pages1104-1113
Number of pages10
ISBN (Print)9783540745488
DOIs
Publication statusPublished - 2007
Event2007 International Conference on Advances in Biometrics, ICB 2007 - Seoul, Korea, Republic of
Duration: 2007 Aug 272007 Aug 29

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4642 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other2007 International Conference on Advances in Biometrics, ICB 2007
CountryKorea, Republic of
CitySeoul
Period07/8/2707/8/29

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Cho, U. K., Hong, J. H., & Cho, S. B. (2007). Automatic fingerprints image generation using evolutionary algorithm. In Advances in Biometrics - International Conference, ICB 2007, Proceedings (pp. 1104-1113). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4642 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-540-74549-5_115