A fingerprint orientation model based on 2D Fourier expansion (FOMFE) and its application to singular-point detection and fingerprint indexing.

Full Abstract

In this paper, we have proposed a fingerprint orientation model based on 2D Fourier expansions (FOMFE) in the phase plane. The FOMFE does not require prior knowledge of singular points (SPs). It is able to describe the overall ridge topology seamlessly, including the SP regions, even for noisy fingerprints. Our statistical experiments on a public database show that the proposed FOMFE can significantly improve the accuracy of fingerprint feature extraction and thus that of fingerprint matching. Moreover, the FOMFE has a low-computational cost and can work very efficiently on large fingerprint databases. The FOMFE provides a comprehensive description for orientation features, which has enabled its beneficial use in feature-related applications such as fingerprint indexing. Unlike most indexing schemes using raw orientation data, we exploit FOMFE model coefficients to generate the feature vector. Our indexing experiments show remarkable results using different fingerprint databases.

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Author information

Author/s: Wang, Yi (Y); Hu, Jiankun (J); Phillips, Damien (D);

Affiliation: School of Computer Science and IT, RMIT University, Melbourne, Australia. yi.wang(-atsign-)computer.org

Journal and publication information

Publication Type: Evaluation Studies; Journal Article; Research Support, Non-U.S. Gov't

Journal: IEEE transactions on pattern analysis and machine intelligence (IEEE Trans Pattern Anal Mach Intell), published in United States. (Language: eng)

Reference: 2007-Apr; vol 29 (issue 4) : pp 573-85

Dates: Created 2007/02/14; Completed 2007/04/24;

PMID: 17299215, status: MEDLINE (last retrieval date: 12/26/2008)

Sourced from the National Library of Medicine. Abstract text and other information may be subject to copyright.

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MeSH headings (categories)

This article was linked to the MESH Headings shown below.

Algorithms
Artificial Intelligence
Biometry - methods
Dermatoglyphics - classification
Fingers - anatomy & histology
Fourier Analysis

Humans
Image Interpretation, Computer-Assisted - methods
Pattern Recognition, Automated - methods
Reproducibility of Results
Sensitivity and Specificity
Signal Processing, Computer-Assisted

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