An improved fingerprint indexing algorithm based on the triplet approach

Kyoungtaek Choi, Dongjae Lee, Sanghoon Lee, Jaihie Kim

Research output: Chapter in Book/Report/Conference proceedingChapter

13 Citations (Scopus)

Abstract

This paper proposes a triplet based fingerprint indexing algorithm which selects the candidates for identification from a large number of enrolled fingerprints. Previous triplet based indexing algorithms have three problems: quantization error, triplet matching error, the proportional increase of similarity score to the number of enrolled triplets. The proposed algorithm solves these problems as follows. First, we generate weighted indices through fuzzy membership functions based on the statistics to reduce quantization error. Second, we apply Geometric Relationships to reduce triplet matching error. Finally, we normalize similarity score to solve the last problem. We compare the proposed algorithm with the previous triplet approach and the Fingercode. Experimental results show that the average rank of the enrolled fingerprint which is identical to an input fingerprint, becomes 2.01 times less than the previous triplet method, and becomes 0.4 times less than the Fingercode.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
EditorsJosef Kittler, Mark S. Nixon
PublisherSpringer Verlag
Pages584-591
Number of pages8
ISBN (Electronic)9783540403029
DOIs
Publication statusPublished - 2003

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume2688
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Choi, K., Lee, D., Lee, S., & Kim, J. (2003). An improved fingerprint indexing algorithm based on the triplet approach. In J. Kittler, & M. S. Nixon (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 584-591). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 2688). Springer Verlag. https://doi.org/10.1007/3-540-44887-x_69