An application for singular point location in fingerprint classification

Ali Ismail Awad, Kensuke Baba

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

1 Citation (Scopus)

Abstract

Singular Point (SP) is one of the local fingerprint features, and it is used as a landmark due its scale and rotation immutability. SP characteristics have been widely used as a feature vector for many fingerprint classification approaches. This paper introduces a new application of singular point location in fingerprint classification by considering it as a reference point to the partitioning process in the proposed pattern-based classification algorithm. The key idea of the proposed classification method is dividing fingerprint into small sub images using SP location, and then, creating distinguished patterns for each class using frequency domain representation for each sub-image. The performance evaluation of the SP detection and the proposed algorithm with different database sub-sets focused on both the processing time and the classification accuracy as key issues of any classification approach. The experimental work shows the superiority of using singular point location with the proposed classification algorithm. The achieved classification accuracy over FVC2002 database subsets is up to 91.4% with considerable processing time and robustness to scale, shift, and rotation conditions.

Original languageEnglish
Title of host publicationDigital Information Processing and Communications - International Conference, ICDIPC 2011, Proceedings
Pages262-276
Number of pages15
EditionPART 1
DOIs
Publication statusPublished - 2011
Externally publishedYes
EventInternational Conference on Digital Information Processing and Communications, ICDIPC 2011 - Ostrava, Czech Republic
Duration: Jul 7 2011Jul 9 2011

Publication series

NameCommunications in Computer and Information Science
NumberPART 1
Volume188 CCIS
ISSN (Print)1865-0929

Conference

ConferenceInternational Conference on Digital Information Processing and Communications, ICDIPC 2011
Country/TerritoryCzech Republic
CityOstrava
Period7/7/117/9/11

Keywords

  • Fingerprint Classification
  • Singular Point
  • Texture Patterns

ASJC Scopus subject areas

  • Computer Science(all)
  • Mathematics(all)

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