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Supervised Deep Learning in Fingerprint Recognition

  • M. Arif Wani
  • Farooq Ahmad Bhat
  • Saduf Afzal
  • Asif Iqbal Khan
Chapter
Part of the Studies in Big Data book series (SBD, volume 57)

Abstract

Fingerprint recognition refers to the process of identifying or confirming the identity of an individual by comparing two fingerprints. Fingerprint recognition is one of the most researched and reliable biometric techniques for identification and authentication. Any system which uses image processing techniques to automatically perform the process of obtaining, storing, analyzing, and matching of a fingerprint with another fingerprint and generating the match is called Automatic Fingerprint Identification System (AFIS). It is a system which takes a fingerprint and picks the most likely matches from millions of fingerprint images stored in the database. With the growth in technology, many algorithms and methods have been proposed so far to automatically match the fingerprints without any human interference or assistance.

Bibliography

  1. 1.
    Arshad, I., Raja, G., Khan, A.: Latent fingerprints segmentation: feasibility of using clustering-based automated approach. Arab. J. Sci. Eng. (Springer Science & Business Media BV) 39(11) (2014)Google Scholar
  2. 2.
    Cao, K., Jain, A.K.: Latent orientation field estimation via convolutional neural network. In: 2015 International Conference on Biometrics (ICB), pp. 349–356. IEEE (2015)Google Scholar
  3. 3.
    Cappelli, R., Maio, D.: The state of the art in fingerprint classification. Autom. Fingerpr. Recognit. Syst., 183–205 (2004)Google Scholar
  4. 4.
    Ezeobiejesi, J., Bhanu, B.: Latent fingerprint image segmentation using fractal dimension features and weighted extreme learning machine ensemble. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, pp. 146–154 (2016)Google Scholar
  5. 5.
    Guo, W., Tang, Y.: Latent fingerprint recognition: challenges and advances. In: Biometric Recognition, pp. 208–215. Springer, Cham (2013)Google Scholar
  6. 6.
    Jain, A.K., Hong, L., Pankanti, S., Bolle, R.: An identity-authentication system using fingerprints. Proc. IEEE 85(9), 1365–1388 (1997)CrossRefGoogle Scholar
  7. 7.
    Khan, A.I., Wani, M.A.: Patch-based segmentation of latent fingerprint images using convolutional neural network. Appl. Artif. Intell. 8, 1–5 (2018)Google Scholar
  8. 8.
    Maltoni, D., Maio, D., Jain, A.K., Prabhakar, S.: Handbook of Fingerprint Recognition. Springer Science & Business Media (2009)Google Scholar
  9. 9.
    Mehtre, B.M., Murthy, N.N., Kapoor, S., Chatterjee, B.: Segmentation of fingerprint images using the directional image. Pattern Recognit. 20(4), 429–435 (1987)Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  • M. Arif Wani
    • 1
  • Farooq Ahmad Bhat
    • 2
  • Saduf Afzal
    • 3
  • Asif Iqbal Khan
    • 4
  1. 1.Department of Computer SciencesUniversity of KashmirSrinagarIndia
  2. 2.Education DepartmentGovernment of Jammu and KashmirKashmirIndia
  3. 3.Islamic University of Science and TechnologyKashmirIndia
  4. 4.Department of Computer SciencesUniversity of KashmirSrinagarIndia

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