Fingerprint indexing based on combination of novel minutiae triplet features

Wei Zhou, Jiankun Hu*, Song Wang, Ian Petersen, Mohammed Bennamoun

*Corresponding author for this work

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

12 Citations (Scopus)

Abstract

Fingerprint indexing is a process of pre-filtering the template database before matching. The most common features used for fingerprint indexing are based on minutiae triplets. In this paper, we investigated the indexing performance based on some commonly used features of minutiae triplets and proposed to combine these features with some novel features of minutiae triplets for fingerprint indexing. Experiments on FVC 2000 DB2a and 2002 DB1a show that the proposed indexing method can perform better than state-of-the-art schemes for full fingerprint indexing, meanwhile, experimental results on NIST SD 14 show that the performance is improved significantly after the new features are added to the feature space, and is fairly good even for partial fingerprint indexing.

Original languageEnglish
Title of host publicationNetwork and System Security - 8th International Conference, NSS 2014, Proceedings
EditorsMan Ho Au, Barbara Carminati, C.-C. Jay Kuo
PublisherSpringer Verlag
Pages377-388
Number of pages12
ISBN (Electronic)9783319116976
DOIs
Publication statusPublished - 2014
Externally publishedYes
Event8th International Conference on Network and System Security, NSS 2014 - Xi’an, China
Duration: 15 Oct 201417 Oct 2014

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8792
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference8th International Conference on Network and System Security, NSS 2014
Country/TerritoryChina
CityXi’an
Period15/10/1417/10/14

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