We apologize for a recent technical issue with our email system, which temporarily affected account activations. Accounts have now been activated. Authors may proceed with paper submissions. PhDFocusTM
CFP last date
20 December 2024
Reseach Article

Correlation based Fingerprint Image Segmentation

by Shekhar R. Suralkar, Pradeep M. Patil
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 68 - Number 7
Year of Publication: 2013
Authors: Shekhar R. Suralkar, Pradeep M. Patil
10.5120/11588-6926

Shekhar R. Suralkar, Pradeep M. Patil . Correlation based Fingerprint Image Segmentation. International Journal of Computer Applications. 68, 7 ( April 2013), 1-3. DOI=10.5120/11588-6926

@article{ 10.5120/11588-6926,
author = { Shekhar R. Suralkar, Pradeep M. Patil },
title = { Correlation based Fingerprint Image Segmentation },
journal = { International Journal of Computer Applications },
issue_date = { April 2013 },
volume = { 68 },
number = { 7 },
month = { April },
year = { 2013 },
issn = { 0975-8887 },
pages = { 1-3 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume68/number7/11588-6926/ },
doi = { 10.5120/11588-6926 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:27:09.561345+05:30
%A Shekhar R. Suralkar
%A Pradeep M. Patil
%T Correlation based Fingerprint Image Segmentation
%J International Journal of Computer Applications
%@ 0975-8887
%V 68
%N 7
%P 1-3
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In this paper, a correlation based fingerprint image segmentation technique is presented. Segmented is a useful image processing tool generally used in Machine vision applications in the Pattern Recognition and classification that leads to the separation of area of interest (AOI) from an image based on some image parameters like gray levels. In this proposed method, direction based segmentation is presented without computing and use of any directional field whose effectiveness has been evaluated for several finger print images (databases like FVC2002, FVC2000).

References
  1. Ratha N. K. , Chen S and Jain A. K. , 'Adaptive flow orientation based feature extraction in fingerprint images', pattern Recognition, Vol. 28, no. 11,pp. 1657-1672, 1995.
  2. S. P. Gupta, 'Statistical Methods', S. Chand, New Delhi, 2002.
  3. Gonzales R. C. and Woods R. E. , "Digital Image Processing," Addison-Wesley, MA, 1992.
  4. Mehtre B. M. , Murthy N. N. , Kapoor S. and Chatterjee B. , "Segmentation of Fingerprint Images Using Directional Image," Pattern Recognition, vol. 20, no. 4, pp 429-435, 1997.
  5. Mehtre B. M. and Chatterjee B. , "Segmentation of Fingerprint Images – A composite Method," Pattern Recognition, vol. 22, no. 4, pp 381-385, 1989.
  6. Ratha N. K. , Chen S. Y. , and Jain A. K. , "Adaptive Flow orientation-Based Feature Extraction in Fingerprint Images," Pattern Recognition, vol. 28, no. 11. pp 1657-1672, 1995.
  7. Maio D. , Maltoni D. , "Direct Gray-Scale Minutiae Detection in Fingerprints," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 19, no. 1, 1997.
  8. Shen L. , Kot A. , and Koo W. M. , "Quality Measures in Fingerprint Images," in Proc. Int. Conf. On Audio – and Video- Based Biometric Person Authentication (3rd), pp 266-271, 2001.
  9. Bazen A. M. , Gerez S. H. , "Segmentation of Fingerprint Images," in Proc. Workshop on Circuits Systems and Signal Processing (ProRISC 2001), pp 276- 280, 2001.
  10. Gonzales R. C. and S. P. Gupta. , "Statistical Methods," S. Chand, New Delhi, 2002.
  11. Database was available on www. bias. csr. unibo. it/fvc2000/download. asp
  12. Maio D. , Maltoni D. , Chappelli R. , Wayman J. L. , and Jain A. K. , "FVC2002: Second Fingerprint Verification Competition," in Proc. Int. Conf. On Pattern Recognition (16th), vol. 3, pp 811 – 814, 2002.
Index Terms

Computer Science
Information Sciences

Keywords

Segmentation Fingerprint Area of Interest (AOI) Correlation