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

Wang, Y, Hu, J and Phillips, D 2007, 'A fingerprint orientation model based on 2D Fourier expansion (FOMFE) and its application to singular-point detection and fingerprint indexing', IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 29, pp. 573-585.


Document type: Journal Article
Collection: Journal Articles

Title A fingerprint orientation model based on 2D Fourier expansion (FOMFE) and its application to singular-point detection and fingerprint indexing
Author(s) Wang, Y
Hu, J
Phillips, D
Year 2007
Journal name IEEE Transactions on Pattern Analysis and Machine Intelligence
Volume number 29
Start page 573
End page 585
Total pages 13
Publisher IEEE
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.
Subject Information Systems not elsewhere classified
Keyword(s) Fields
Classification
Computation
DOI - identifier 10.1109/tpami.2007.1003
Copyright notice © 2007 IEEE
ISSN 0162-8828
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Citation counts: TR Web of Science Citation Count  Cited 172 times in Thomson Reuters Web of Science Article | Citations
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