2020
DOI: 10.1049/iet-bmt.2019.0121
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Fingerprint enhancement using multi‐scale classification dictionaries with reduced dimensionality

Abstract: In order to improve the quality of fingerprint with a large noise, this study proposes a fingerprint enhancement method by using a sparse representation of learned multi-scale classification dictionaries with reduced dimensionality. The multi-scale dictionary is used to balance the contradiction between the accuracy and the anti-noise ability, which is an ideal solution to reconcile the demands of enhancement quality and computational performance. The principal component analysis is applied in the authors' tec… Show more

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Cited by 2 publications
(1 citation statement)
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“…Liu et al [38] propose multi-scale sparse coded dictionaries for enhancement. Xu et al [39] learn multi-scale dictionaries and exploit principal component analysis (PCA) for reducing dimensionality of dictio-naries. Fingerprint image is enhanced using these dictionaries and spectra diffusion.…”
Section: Fingerprint Enhancementmentioning
confidence: 99%
“…Liu et al [38] propose multi-scale sparse coded dictionaries for enhancement. Xu et al [39] learn multi-scale dictionaries and exploit principal component analysis (PCA) for reducing dimensionality of dictio-naries. Fingerprint image is enhanced using these dictionaries and spectra diffusion.…”
Section: Fingerprint Enhancementmentioning
confidence: 99%