Fingerprint Matching Using the Distribution of the Pairwise Distances Between Minutiae

Park, Chul-Hyun; Smith, M.J.T.; Boutin, Mireille; Lee, Joon-Jae

doi:10.1007/11527923_72

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2022

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Cited by 5 publications

(2 citation statements)

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“…However, this method can only perform a coarse fingerprint authentication, and cannot handle big translations and rotations. Park et al proposed a feature vector based on the distribution of the pairwise distances between minutiae [12]. However, this algorithm is only evaluated on the manually labeled minutiae and the performance is not satisfying.…”

Section: Introductionmentioning

confidence: 99%

Complex spectral minutiae representation for fingerprint recognition

Veldhuis

2010

2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops

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Section: Introductionmentioning

confidence: 99%

Complex spectral minutiae representation for fingerprint recognition

Veldhuis

2010

2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops

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“…However, this method can only perform a coarse fingerprint authentication, and cannot handle big translations and rotations. Recently, a feature vector based on the distribution of the pairwise distances between minutiae is proposed by Park et al [13]. However, this algorithm is only evaluated on the manually labelled minutiae and the performance is not satisfying.…”

Section: Introductionmentioning

confidence: 99%

Spectral minutiae: A fixed-length representation of a minutiae set

Veldhuis

Kevenaar

et al. 2008

2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops

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Minutiae, which are the endpoints and bifurcations of fingerprint ridges, allow a very discriminative classification of fingerprints. However, a minutiae set is an unordered set and the minutiae locations suffer from various deformations such as translation, rotation and scaling. In this paper, we introduce a novel 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. By applying the spectral minutiae representation, we can combine the fingerprint recognition system with a template protection scheme, which requires a fixed-length feature vector. This paper also presents two spectral minutiae matching algorithms and shows experimental results.

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Fingerprint—A Survey on Feature Transformation

Mohsin

Bharti

2022

Advances in Intelligent Systems and Computing

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Fingerprint Matching Using the Distribution of the Pairwise Distances Between Minutiae

Cited by 5 publications

References 6 publications

Complex spectral minutiae representation for fingerprint recognition

Complex spectral minutiae representation for fingerprint recognition

Spectral minutiae: A fixed-length representation of a minutiae set

Fingerprint—A Survey on Feature Transformation

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