A Fast Minutiae-Based Fingerprint Recognition System

The spectral minutiae representation is a method to represent a minutiae set as a fixed-length feature vector, which is invariant to translation, and in which rotation and scaling become translations, so that they can be easily compensated for. These characteristics enable the combination of fingerp...

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Bibliographic Details
Published in:IEEE systems journal 2009-12, Vol.3 (4), p.418-427
Main Authors: Haiyun Xu, Veldhuis, R.N.J., Kevenaar, T.A.M., Akkermans, T.A.H.M.
Format: Article
Language:English
Subjects:
Airports
Algorithms
Biometrics
Costs
Discrete Fourier transforms
fast minutiae matching
feature reduction
fingerprint identification
Fingerprint recognition
Fingerprinting
Fingerprints
Fourier transforms
Identification systems
Laboratories
Large-scale systems
Matching
Mathematical analysis
Principal component analysis
Principal components analysis
Protection
Recognition
Reduction
Spatial databases
Spectra
template protection
Vectors (mathematics)
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Summary:The spectral minutiae representation is a method to represent a minutiae set as a fixed-length feature vector, which is invariant to translation, and in which rotation and scaling become translations, so that they can be easily compensated for. These characteristics enable the combination of fingerprint recognition systems with template protection schemes that require as an input a fixed-length feature vector. Based on the spectral minutiae features, this paper introduces two feature reduction algorithms: the Column Principal Component Analysis and the Line Discrete Fourier Transform feature reductions, which can efficiently compress the template size with a reduction rate of 94%. With reduced features, we can also achieve a fast minutiae-based matching algorithm. This paper presents the performance of the spectral minutiae fingerprint recognition system and shows a matching speed with 125 000 comparisons per second on a PC with Intel Pentium D processor 2.80 GHz and 1 GB of RAM. This fast operation renders our system suitable as a preselector for a large-scale fingerprint identification system, thus significantly reducing the time to perform matching, especially in systems operating at geographical level (e.g., police patrolling) or in complex critical environments (e.g., airports).
ISSN:1932-8184
1937-9234
DOI:10.1109/JSYST.2009.2034945