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Bio-medical and latent fingerprint enhancement and matching using advanced scalable soft computing models

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Abstract

Latent fingerprints are acquired from crime places which are utilized to distinguish suspects in crime inspection. In general, latent fingerprints contain mysterious ridge and valley structure with nonlinear distortion and complex background noise. These lead to fundamentally difficult problem for further analysis. Hence, the image quality is required for matching those latent fingerprints. In this work, we develop a model for enhancement of latent fingerprint and matching algorithm, which requires manually marked (ground-truth) ROI latent fingerprints. This 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, these algorithms have been figured based on minutiae and SIFT 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 Fingerprint Verification Competition − 2004 (FVC-2004) and Indraprastha Institute of Information Technology (IIIT)-latent fingerprint which indicates that by fusing the proposed enhancement algorithm, the matching precision has fundamentally moved forward.

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Acknowledgements

The authors wish to express their sincere thanks to the referees and the editor for their valuable comments and suggestions to improve the quality of the paper.

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Authors and Affiliations

  1. School of Advanced Sciences, VIT, Vellore, India

    Adhiyaman Manickam & Ezhilmaran Devarasan

  2. University of California, Davis, USA

    Gunasekaran Manogaran

  3. Department of Computer Science and Computer Engineering, LaTrobe University, Melbourne, Australia

    Naveen Chilamkurti

  4. School of Computer Science and Engineering, VIT, Vellore, India

    Vijayarajan Vijayan & Shubham Saraff

  5. SCOPE, VIT, Chennai, India

    R. D. Jackson Samuel

  6. Department of Electronics and Communication Engineering, CMR Engineering College, Hyderabad, Telangana, India

    Raja Krishnamoorthy

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  1. Adhiyaman Manickam
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  2. Ezhilmaran Devarasan
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  3. Gunasekaran Manogaran
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  8. Raja Krishnamoorthy
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Correspondence to Gunasekaran Manogaran.

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Manickam, A., Devarasan, E., Manogaran, G. et al. Bio-medical and latent fingerprint enhancement and matching using advanced scalable soft computing models. J Ambient Intell Human Comput 10, 3983–3995 (2019). https://doi.org/10.1007/s12652-018-1152-1

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  • DOI: https://doi.org/10.1007/s12652-018-1152-1

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