Advertisement

Review on Implementation of Fingerprint Verification System Using Image Inpainting

  • Milind B. BhilavadeEmail author
  • Meenakshi R. Patil
  • Lalita S. Admuthe
  • K. S. Shivaprakasha
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 614)

Abstract

Biometric attendance system has become more popular over the conventional system due to its various advantages. Fingerprint verification system is one of the promising methods installed in various organizations for attendance purpose. Usage of image inpainting technique in fingerprint verification improves the performance of fingerprint verification system. This paper highlights on some image inpainting techniques useful in fingerprint verification system. This paper also focuses on motivation to use image inpainting in fingerprint verification system. The fingerprint verification system is proposed where image inpainting algorithm shall be used to improve the performance of fingerprint verification system.

Keywords

Fingerprint Minutiae Ridge Pores Image inpainting 

References

  1. 1.
    Agrawal P, Kapoor R, Agrawal A (2014) A Hybrid partial fingerprint matching algorithm for estimation of equal error rate. In: Proceedings of ICACCCT 2014, ISBN No. 978-1-4799-3914-5/14/$31.00 ©2014 IEEE pp 1295–1299Google Scholar
  2. 2.
    Jain AK, Chen Y, Demirkus M (2007) Pores and ridges: high-resolution fingerprint matching using Level 3 features college. IEEE Trans Pattern Anal Mach Intell 29(1):15–27CrossRefGoogle Scholar
  3. 3.
    Cappelli R, Lumini A, Maio D, Maltoni D (2007) Fingerprint image reconstruction from standard templates. IEEE Trans Pattern Anal Mach Intell 29(9):1489–1503CrossRefGoogle Scholar
  4. 4.
    Cao K, Jain AK (2015) Learning fingerprint reconstruction from Minutiae Image. IEEE Trans Inf Forensic Secur 10(1):104–117CrossRefGoogle Scholar
  5. 5.
    Arora SS, Liu E, Cao K, Jain AK (2014) Latent fingerprint matching: performance gain via feedback from exemplar prints. IEEE Trans Pattern Anal Mach Intell 36(12):2452–2465CrossRefGoogle Scholar
  6. 6.
    Guillemot C, Le Meur O (2014) Image inpainting. IEEE Signal Process Mag, pp 127–144Google Scholar
  7. 7.
    Park CH, Lee JJ, Smith MJT, Park Sl, Park KH (2004) Directional filter bank-based fingerprint feature extraction and matching. IEEE Trans Circuits Syst Video Technol 14(1):74–85CrossRefGoogle Scholar
  8. 8.
    Moayer B, Fu KS (1976) A tree system approach for fingerprint pattern recognition. IEEE Trans Comput C-25(3):262–274CrossRefGoogle Scholar
  9. 9.
    Feng J, Jain AK (2011) Fingerprint reconstruction: from minutiae to phase. IEEE Ttransactions Pattern Anal Mach Intell 33(2):209–223CrossRefGoogle Scholar
  10. 10.
    Carola-Bibiane (2009) Modern PDE techniques for image inpainting. Ph.D. thesis submitted to DAMTP Centre for mathematical sciences, University of Cambridge [online] available: http://www.damtp.cam.ac.uk/user/cbs31/Publications_files/thesis.pdf
  11. 11.
    Hasegawa M, Kako T, Hirobayashi S, Misawa T, Yoshizawa T, Inazumi Y (2013) Image inpainting on the basis of spectral structure from 2-D Nonharmonic analysis. IEEE Trans Image Process 22(8):3008–3017MathSciNetCrossRefGoogle Scholar
  12. 12.
    He L, Wang Y (2014) Iterative support detection-based split bregman method for wavelet frame-based image inpainting. IEEE Trans Image Process 23(12):5470–5485MathSciNetCrossRefGoogle Scholar
  13. 13.
    Bertalmío M (2006) Strong-continuation, contrast-invariant inpainting with a third-order optimal PDE. IEEE Trans Image Process 15(7):1934–1938CrossRefGoogle Scholar
  14. 14.
    Wohlberg B (2011) Inpainting by joint optimization of linear combinations of exemplars. IEEE Signal Process Lett 18(1):75–78CrossRefGoogle Scholar
  15. 15.
    Liu Yunqiang, Caselles Vicent (2013) Exemplar-based image inpainting using multiscale graph cuts. IEEE Trans Image Process 22(5):1699–1711MathSciNetCrossRefGoogle Scholar
  16. 16.
    Ruži´c T, Pižurica A (2015) Context-aware patch-based image inpainting using markov random field modeling. IEEE Trans Image Process 24(1) pp 444–456Google Scholar
  17. 17.
    Awati AS, Deshpande SP, Belagal PY, Patil M (2017) Digital image inpainting using modified Kriging algorithm. In: Proceedings of 2nd international conference for convergence in technology (I2CT) available online at IEEExplore pp 945–950Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  • Milind B. Bhilavade
    • 1
    Email author
  • Meenakshi R. Patil
    • 2
  • Lalita S. Admuthe
    • 3
  • K. S. Shivaprakasha
    • 4
  1. 1.Electrical Engineering DepartmentVTUBelagaviIndia
  2. 2.Electronics and Communication Engineering DepartmentJain AGM Institute of TechnologyJamkhandiIndia
  3. 3.Electronics Engineering DepartmentDKTE’S Textile and Engineering InstituteIchalkaranjiIndia
  4. 4.Electronics and Communication Engineering DepartmentNMAMITUdupiIndia

Personalised recommendations