Fingerprint image segmentation based on multi-features histogram analysis

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

Abstract

An effective fingerprint image segmentation based on multi-features histogram analysis is presented. We extract a new feature, together with three other features to segment fingerprints. Two of these four features, each of which is related to one of the other two, are reciprocals with each other, so features are divided into two groups. These two features' histograms are calculated respectively to determine which feature group is introduced to segment the aim-fingerprint. The features could also divide fingerprints into two classes with high and low quality. Experimental results show that our algorithm could classify foreground and background effectively with lower computational cost, and it can also reduce pseudo-minutiae detected and improve the performance of AFIS.

Original languageEnglish
Title of host publicationMIPPR 2007
Subtitle of host publicationAutomatic Target Recognition and Image Analysis; and Multispectral Image Acquisition
DOIs
StatePublished - 2007
Externally publishedYes
EventMIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition - Wuhan, China
Duration: 15 Nov 200717 Nov 2007

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume6786
ISSN (Print)0277-786X

Conference

ConferenceMIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition
Country/TerritoryChina
CityWuhan
Period15/11/0717/11/07

Keywords

  • Biometrics
  • Fingerprint
  • Histogram
  • Segmentation

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