CFP last date
20 December 2024
Call for Paper
January Edition
IJCA solicits high quality original research papers for the upcoming January edition of the journal. The last date of research paper submission is 20 December 2024

Submit your paper
Know more
The week's pick
Responsive image
Improved Shuffled Frog Leaping Algorithm with Self-Adaptive Shuffling for Fuzzy Logic PD+G Controller Optimization in Robotic Manipulators

Duc Hoang Nguyen
Random Articles
Reseach Article

Fingerprint Ridge Orientation Extraction: A Review of State of the Art Techniques

by Vidaydevi G. Biradar, Sarojadevi H.
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 91 - Number 3
Year of Publication: 2014
Authors: Vidaydevi G. Biradar, Sarojadevi H.
10.5120/15859-4773

Vidaydevi G. Biradar, Sarojadevi H. . Fingerprint Ridge Orientation Extraction: A Review of State of the Art Techniques. International Journal of Computer Applications. 91, 3 ( April 2014), 8-13. DOI=10.5120/15859-4773

@article{ 10.5120/15859-4773,
author = { Vidaydevi G. Biradar, Sarojadevi H. },
title = { Fingerprint Ridge Orientation Extraction: A Review of State of the Art Techniques },
journal = { International Journal of Computer Applications },
issue_date = { April 2014 },
volume = { 91 },
number = { 3 },
month = { April },
year = { 2014 },
issn = { 0975-8887 },
pages = { 8-13 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume91/number3/15859-4773/ },
doi = { 10.5120/15859-4773 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:11:47.304602+05:30
%A Vidaydevi G. Biradar
%A Sarojadevi H.
%T Fingerprint Ridge Orientation Extraction: A Review of State of the Art Techniques
%J International Journal of Computer Applications
%@ 0975-8887
%V 91
%N 3
%P 8-13
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Personal identification based on fingerprints is very popular compared to identification based on other biometric features like iris, gait and face etc. Performance of automatic fingerprints identification systems depends upon the quality of fingerprints. Extraction of fingerprints features in poor quality fingerprints is challenging task. Accurate measurement of fingerprints feature improves the accuracy of identification systems. Fingerprints consists of ridge and valley structures and offers different types of features, they are categorized as level 1, level 2 and level 3 features. Level 1 features are singular points which are used for fingerprints registration, classification etc. Level 2 features are ridge features like minutiae points, ridge orientation etc. , and commercially available fingerprint recognition systems are based on level 2 features. Level 3 features include sweat pores, incipient ridges etc. Among these features ridge orientation is used for fingerprint enhancement, fingerprint classification, indexing and fingerprint segmentation. This paper provides an overview of existing state of the art techniques for ridge orientation estimation.

References
  1. Davide Maltoni, Dario Maio, Anil K. Jain, Salil Prabhakar, L. L. 2009. Handbook of Fingerprint Recognition.
  2. Asker M. Bazen, Sabih H. Gerez, "Systematic Methods for the Computation of the Directional Fields and Singular Points of Fingerprints", IEEE Transactions On Pattern Analysis And Machine Intelligence, Vol. 24, No. 7, July 2002
  3. Jie Zhou, Jinwei Gu, "A Model-Based Method for the Computation of Fingerprints' Orientation Field", IEEE Transactions On Image Processing, Vol. 13, No. 6, June 2004.
  4. J. Gu, J. Zhou, D. Zhang, "A combinational model for orientation field of fingerprints", Pattern Recogn,37(3), pp. 543-553, 2004.
  5. Wei-Yun Yau, Jun Li, Han Wang, J. 2004. Nonlinear phase portrait modelling of fingerprint orientation. In proceedings of ICARCV on Control, Automation, Robotics and Vision.
  6. Asker M. Bazen, Niek J. Bouman, and Raymond N. J. Veldhuis, J 2004. A Multi-Scale Approach to Directional Field Estimation. In proceedings of RISC 2004.
  7. S. Dass, "Markov Random Field Models for Directional Field and Singularity Extraction in Fingerprint Images", IEEE Trans. Image Processing, vol. 13, no. 10, pp. 1358-1367, 2004.
  8. En Zhu, Jian-Ping Yin, Guo-Min Zhang, Chun-Feng Hu, J. 2006. Fingerprint Ridge Orientation Estimation Based On Neural Network, in proceedings Of Wseas Int. Conf. On Signal Processing, Robotics and Automation.
  9. Yi Wang, Jiankun Hu, Damien Phillips, "A Fingerprint Orientation Model Based On 2d Fourier Expansion (FOMFE) and Its Application to Singular-Point Detection and Fingerprint Indexing", IEEE Transactions On Pattern Analysis and Machine Intelligence, Vol. 29, No. 4, pp. 573-585, 2007.
  10. Yi Wang, Jiankun Hu, Fengling Han, "Enhanced gradient-based algorithm for the estimation of fingerprint orientation fields", Applied Mathematics and Computation, pp. 823–833, vol. 185, 2007.
  11. Xudong Jiang, "Extracting image orientation feature by using integration operator", Pattern Recognition, pp. 705 – 717, vol. 40, 2007.
  12. Qinzhi Zhang, Hong Yan, "Fingerprint Orientation Field Interpolation Based On The Constrained Delaunay Triangulation", International Journal Of Information And Systems Sciences Volume 3, Number 3, Pages 438–452, 2007.
  13. Luping Ji, Zhang Yi, "Fingerprint orientation field estimation using ridge projection", Pattern Recognition , Vol. 41 ,pp. 1491 – 1503, 2008.
  14. Carsten Gottschlich, Preda Mihailesc, Axel Munk, "Robust Orientation Field Estimation and Extrapolation Using Semilocal Line Sensors", IEEE transactions on Image and Signal Processing and analysis, pp. 529-533. 2009.
  15. Surinder Ram, Horst Bischof Josef Birchbauer, J. 2009. Active fingerprint ridge orientation models. In proceedings of ICB '09(Third International Conference on Advances in Biometrics).
  16. Surinder Ram, Horst Bischof, Josef Birchbauer, "Modelling fingerprint ridge orientation using legendre polynomials", Pattern Recogn. , vol 43,342-357, 2010.
  17. Limin Liu , Tian-Shyr Dai, "A Reliable Fingerprint Orientation Estimation Algorithm", Journal of Information Science and Engineering, vol. 27, pp. 353-368, 2011.
  18. S. Yoon, J. Feng, A. Jain, J. 2011. Latent ?ngerprint enhancement via robust orientation ?eld estimation. In proceedings of IJCB ( International Joint Conference on Biometrics.
  19. Francesco Turroni, Davide Maltoni, Raffaele Cappelli, Dario Maio, "Improving Fingerprint Orientation Extraction", IEEE Transactions On Information Forensics And Security, Vol. 6, No. 3, pp. 1002-1013 , 2011.
  20. Jianjiang Feng, Jie Zhou, Anil K. Jain, "Orientation field estimation for latent fingerprint enhancement", IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 54, no. 4, pp. 925–940, 2013.
  21. Prasad Reddy P. V. G. D, M. James Stephen, "Towards Accurate Estimation of Fingerprint Ridge Orientation Using BPNN and Ternarization", IOSR Journal of Computer pp. 2278-8727, Vol 13,. 2013.
Index Terms

Computer Science
Information Sciences

Keywords

Fingerprint recognition Ridge orientation combinational model Latent Gradients Singular points.

Powered by PhDFocusTM