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Issue:Intuitionistic fuzzy system based latent fingerprint enhancement and matching using minutiae and SIFT feature

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Title of paper: Intuitionistic fuzzy system based latent fingerprint enhancement and matching using minutiae and SIFT feature
Author(s):
Adhiyaman Manickam
Department of Mathematics, School of Advanced Science, VIT University, Vellore, India
adhimsc2013@gmail.com
Ezhilmaran Devarasan
Department of Mathematics, School of Advanced Science, VIT University, Vellore, India
ezhil.devarasan@yahoo.com
Published in: Notes on Intuitionistic Fuzzy Sets, Volume 24 (2018), Number 1, pages 87–98
DOI: https://doi.org/10.7546/nifs.2018.24.1.87-98
Download:  PDF (749 Kb  Kb, Info)
Abstract: In this work, we developed a model for latent fingerprint enhancement and matching algorithm, which requires manually marked ROI latent fingerprints. The proposed model includes two phases (i) Latent fingerprints contrast enhancement using type-2 intuitionistic fuzzy set (ii) Extract the minutiae and Scale Invariant Feature Transformation (SIFT) features from the latent fingerprint image. For matching, this algorithm has been figured based on minutiae and SIFTS points which inspect n number of images and the scores are calculated by Euclidean distance. We tested our algorithm for matching, using some public domain fingerprint databases such as FVC-2004 and IIIT-latent fingerprint which indicates that by fusing the proposed enhancement algorithm, the matching precision has fundamentally moved forward.
Keywords: Latent fingerprint image, Type-2 intuitionistic fuzzy set, Feature extraction, Enhancement, Matching
AMS Classification: 94Dxx, 03E72, 03B52, 93C42.
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