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Reseach Article

An Effective Human Fingerprint Segmentation Method using Watershed Algorithm

by Pinaki Pratim Acharjya, Dibyendu Ghoshal
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 53 - Number 13
Year of Publication: 2012
Authors: Pinaki Pratim Acharjya, Dibyendu Ghoshal
10.5120/8482-2422

Pinaki Pratim Acharjya, Dibyendu Ghoshal . An Effective Human Fingerprint Segmentation Method using Watershed Algorithm. International Journal of Computer Applications. 53, 13 ( September 2012), 23-26. DOI=10.5120/8482-2422

@article{ 10.5120/8482-2422,
author = { Pinaki Pratim Acharjya, Dibyendu Ghoshal },
title = { An Effective Human Fingerprint Segmentation Method using Watershed Algorithm },
journal = { International Journal of Computer Applications },
issue_date = { September 2012 },
volume = { 53 },
number = { 13 },
month = { September },
year = { 2012 },
issn = { 0975-8887 },
pages = { 23-26 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume53/number13/8482-2422/ },
doi = { 10.5120/8482-2422 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:54:32.655705+05:30
%A Pinaki Pratim Acharjya
%A Dibyendu Ghoshal
%T An Effective Human Fingerprint Segmentation Method using Watershed Algorithm
%J International Journal of Computer Applications
%@ 0975-8887
%V 53
%N 13
%P 23-26
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

For more than a century fingerprints ware considered to be the identifying mark for the human beings. Fingerprint is a protected human organ and an effective biometric approach to human or personal identification. It acts like living passwords for humans as its texture is stable throughout the human life. Fingerprints are an impression left by the friction ridges of human finger. This paper contains a very useful image segmentation method for fingerprints segmentation by taking the idea from friction ridges of human finger and also with an effective storage capacity for the segmented images. Watershed algorithm depends on ridges to perform a proper segmentation, a property that is often fulfilled in contour detection where the boundaries of the objects are expressed as ridges. The tool we have used is MAT LAB, typically using the MAT LAB editor.

References
  1. C. Gonzalez, Richard E. Woods, Digital Image Processing , Addison westly pub. company.
  2. C. Gonzalez, Richard E. Woods, Digital Image Processing , Addison westly pub. company.
  3. L. Vincent and P. Soille, "Watersheds in digital spaces: an efficient algorithm based on immersion simulations," IEEE Trans. Pattern Anal. Mach. Intell. , vol. 13, no. 6, pp. 583-598, Jun. 1991.
  4. S. Beucher, "Watersheds of functions and picture segmentation," in Proc. IEEEInt. Conf. Acoustic, Speech, Signal Processing, pp. 1982-`931, 1982.
  5. Gonzalez & Woods, Digital Image Processing, 3rd edition, Prentice Hall India, 2008.
  6. P. Jackway, "Gradient watersheds in morphological scale space," IEEE Trans. Image Processing vol. l5, pp. 913–921, June, 1996.
  7. S. Beucher, "Watershed, hierarchical segmentation and water fall algorithm," in Mathematical Morphology and Its Applications to Image Processing, Dordrecht, The Netherlands: Kluwer, 1994, pp. 69–76.
  8. E. N. Mortrnsen and W. A. Barrett, "Toboggan-based intelligent scissors with a four-paramreer edge model," in Proc. IEEE Conf. Computer Vision and Pattern Recognition, pp. 452-458, 1999.
  9. Vicent L. Solille P, Watershed in digital spaces, "An efficient algorithm based immersion simulations," IEEE Transections PAMI, pp. 538-598, 1991.
  10. M. Couprie and G. Bertrand, "Topological grayscale watershed transformation," in Proc. SPIE Vision Geometry V, vol. 3168, pp. 136-146, 1997.
  11. C. Riddell, p. Brigger, R. E. Carson and S. L. Bacharach, "The watershed algorithm: a method to segment noisy PET transmission images," IEEE Trans. Nucl. Sci. , vol. 46, no. 3, pp. 713-719, Mar, 1999.
  12. M. W. Hansen and W. E. Higgins, "Watershed-based maximum-homogeneity filtering," IEEE Trans. Image Process. , vol. 8, no. 7, pp. 982-988, jul. 1999.
  13. U. Halici, Turkey,L. C. Jain, " Introduction to finger print Recognition," Australia & A. Erol, Turkey.
  14. J. Berry, "The history and development of fingerprinting," in Advances in Fingerprint Technology, (H. C. Lee and R. E. Gaensslen, ed. s), CRC Press, Florida, 1994, pp. 1-38, 1994.
  15. W. S. Chen and C. L. Kuo, "Apparatus for Imaging Fingerprint or Topgraphic Relief Pattern on the Surface of an Object," US Patent 5448649, 1995.
  16. A. K. Jain, L. Hong, S. Pankanti, and R. Bolle, "An Identity-Authentication System Using Fingerprints," Proceedings of the IEEE, Vol. 85, No. 9, pp. 1365-1388, 1997.
  17. K. Haris,"Hybrid image segmentation using watersheds and fast region merging," IEEE Trans Image Processing, 7(12), pp. 1684-1699, 1998.
  18. F. Meyer, S. Beucher, "Morphological Segmentation," Journal of Visual Communication and Image Representation, 1, pp. 21-46, 1990.
  19. D. Wang, "Unsupervised video segmentation based on waterseds and temporal traking," IEEE Trans. Circuits Syst. VideoTechnol. , vol. 8, no. 5, pp. 539-546, May 1998.
  20. Rafael C. Gonzalez, Richard E. Woods, Steven L. Eddins, "Digital Image Processing Using MATLAB," Second Edition, Gatesmark Publishing, 2009
Index Terms

Computer Science
Information Sciences

Keywords

Image segmentation Fingerprints Watershed Algorithm