CFP last date
20 May 2024
Reseach Article

Gabor Filter-based Multiple Enrollment Fingerprint Recognition

by Fred Kaggwa, John Ngubiri, Florence Tushabe
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 139 - Number 7
Year of Publication: 2016
Authors: Fred Kaggwa, John Ngubiri, Florence Tushabe

Fred Kaggwa, John Ngubiri, Florence Tushabe . Gabor Filter-based Multiple Enrollment Fingerprint Recognition. International Journal of Computer Applications. 139, 7 ( April 2016), 32-38. DOI=10.5120/ijca2016909210

@article{ 10.5120/ijca2016909210,
author = { Fred Kaggwa, John Ngubiri, Florence Tushabe },
title = { Gabor Filter-based Multiple Enrollment Fingerprint Recognition },
journal = { International Journal of Computer Applications },
issue_date = { April 2016 },
volume = { 139 },
number = { 7 },
month = { April },
year = { 2016 },
issn = { 0975-8887 },
pages = { 32-38 },
numpages = {9},
url = { },
doi = { 10.5120/ijca2016909210 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
%0 Journal Article
%1 2024-02-06T23:40:21.249735+05:30
%A Fred Kaggwa
%A John Ngubiri
%A Florence Tushabe
%T Gabor Filter-based Multiple Enrollment Fingerprint Recognition
%J International Journal of Computer Applications
%@ 0975-8887
%V 139
%N 7
%P 32-38
%D 2016
%I Foundation of Computer Science (FCS), NY, USA

Minutiae-based matching techniques have been widely used in the implementation of multiple enrollment fingerprint recognition systems. However, these techniques suffer the difficulty of automatically extracting all minutiae points due to failure to detect the complete ridge structures of a fingerprint. With poor quality fingerprint images, detection of minutiae points as well as describing all the local ridge structures is difficult. It is also difficult to quickly match two fingerprints that have a difference in the number of unregistered minutiae. Non-minutiae based techniques such as Gabor filtering are rich in terms of distinguishing features and can be used as an alternative since they capture both the local and global details in a fingerprint. This paper presents a Gabor filter-based approach; the first of the kind to implement a verification multiple enrollment based fingerprint recognition system. The Gabor filter-based multiple enrollment fingerprint recognition method was compared with a spectral minutiae-based method using two fingerprint databases; FVC 2000-DB2-A and FVC 2006-DB2-A. Although the minutiae-based method outperformed the Gabor filter-based method, the results attained from the later are promising and can be a good basis for implementing Gabor filter-based techniques in designing multiple enrollment based fingerprint systems.

  1. Amira Saleh, Ayman Bahaa and A. Wahdan,“fingerprint Recognition,” Computer and systems engineering department Faculty of Engineering /Ain Shams University, Egypt, 2011.
  2. Anil K. Jain, Fellow, IEEE, Salil Prabhakar, Lin Hong, and Sharath Pankanti, “Filterbank-Based Fingerprint Matching,” IEEE Transactions On Image Processing, vol. 9, No. 5, 2000.
  3. Ishpreet Singh Virk and Raman Maini,“Fingerprint Image Enhancement and Minutiae Matching in Fingerprint Verification”, Journal of Computing Technologies, vol. 1, Jun. 2012.
  4. Urvashi Chaudhary and Shruti Bhardwaj,“Fingerprint image enhancement and minutia extraction,” International Journal of Advance Research in Computer Science and Management Studies, vol. 2, Issue 5, 2014.
  5. Raymond Thai, “Fingerprint Image Enhancement and Minutiae Extraction, the School of Computer Science and Software Engineering, the University of Western Australia, 2003.
  6. Prateek Verma, Maheedhar Dubey, Praveen Verma, ”Correlation based method for identification of fingerprint- a biometricapproach,” International Journal of Engineering and Advanced Technology (IJEAT), ISSN: 2249 – 8958, vol. 1, Issue 4, 2012.
  7. Manvjeet Kaur, Mukhwinder Singh, Akshay Girdhar, and Parvinder S. Sandhu, “Fingerprint Verification System using Minutiae Extraction Technique”, World Academy of Science, Engineering and Technology 46 2008.
  8. Munir, M. U., Javed, M. Y., ''Fingerprint Matching using Gabor Filters,'' 2005.
  9. E. Zhu, J. Yin, G. Zhang and C. Hu, “A Gabor filter based fingerprint enhancement scheme using average frequency", Int. Journal of Pattern Recog. and Artif. Intell., vol. 20, no. 3, pp. 417-429, 2006.
  10. C. J. Lee and S. D. Wang, “A Gabor filter-based approach to fingerprint recognition", Proc. IEEE Workshop on Signal Processing Systems (SiPS), pp. 371-378, 1999.
  11. F. Alonso-Fernandez, J. Fierrez-Aguilar and J. Ortega-Garcia, “An enhanced Gabor filter-based segmentation algorithm for fingerprint recognition systems", Proc. 4th Int. Symposium on Image and Signal Processing and Analysis (ISPA2), Zagreb, Croatia, pp. 239-244, 2005.
  12. A. K. Jain, A. Ross, and S. Prabhakar, "Fingerprint Matching Using Minutiae and Texture Features", Proc International Conference on Image Processing (ICIP), pp. 282-285, Greece, October 7-10, 2001.
  13. S. Prabhakar, “Gabor filter bank based Fingerprint classification and identification.”, PhD. Thesis, Department of Computer Engg., MSU
  14. Dhruv Batra, Girish Singhal and Santanu Chaudhury: Gabor Filter based Fingerprint Classification using Support Vector Machines, IEEE INDIA ANNUAL CONFERENCE 2004, INDICON 2004
  15. B. Garg, A. Chaudhary, K. Mendiratta and V. Kumar, "Fingerprint recognition using Gabor Filter," Computing for Sustainable Global Development (INDIACom), 2014 International Conference on, New Delhi, 2014, pp. 953-958.
  16. M. U. Munir, M. Y. Javed, “Fingerprint Matching Using Gabor Filters In National Conference on Emerging Technologies (2004), pp. 147-151”
  17. Bazen, Asker M., et al. "A Correlation-Based Fingerprint Verification System." (2000): 205-213.
  18. Nandakumar, Karthik, and Anil K. Jain. "Local correlation-based fingerprint matching." In Indian Conference on Computer Vision, Graphics and Image Processing. 2004.
  19. Krithika Venkataramani and B. V. K. Vijaya Kumar. 2003. Fingerprint verification using correlation filters. In Proceedings of the 4th international conference on Audio- and video-based biometric person authentication (AVBPA'03), Josef Kittler and Mark S. Nixon (Eds.). Springer-Verlag, Berlin, Heidelberg, 886-894.
  20. Almudena Lindoso, Luis Entrena, Judith Liu-Jimenez, and Enrique San Millan. 2007. Correlation-based fingerprint matching with orientation field alignment. In Proceedings of the 2007 international conference on Advances in Biometrics (ICB'07), Seong-Whan Lee and Stan Z. Li (Eds.). Springer-Verlag, Berlin, Heidelberg, 713-721.
  21. Alonso-Fernandez, Fernando, J. Fierrez, and Javier Ortega-Garcia. "An enhanced gabor filter-based segmentation algorithm for fingerprint recognition systems." Proc. IEEE Intl. Symposium on Image and Signal Processing and Analysis, ISPA, Spec. Sess on. Signal Image Processing for Biometrics, IEEE Press, Zagreb (Croatia), September 2005. University of Zagreb, 2005.
  22. Elmir, Youssef, et al. "Personal Identification by Fingerprints based on Gabor Filters." CIIA. 2009.
  23. Segaran, Toby. Programming Collective Intelligence: Building Smart Web 2. 0 Applications. Danbury: O'Reilly Media, Incorporated, 2007. Print.
  24. Mane, Arjun V., Yogesh S. Rode, and K. V. Kale. "Novel Multiple Impression based Multimodal Fingerprint Recognition System." International Journal of Computer Applications 27 (2011).
  25. Simon-Zorita D., Ortega-Garcia J., Sanchez-Asenjo M. and Gonzalez-Rodriguez J., “Facing Position Variability in Minutiae-Based Fingerprint Verification Through Multiple References and Score Normalization Techniques,” in Proc. Int. Conf. on Audio- and Video-Based Biometric Person authentication (4th), pp. 214–223, 2003a.
  26. C. Ren, Y. Yin, J. Ma, and G. Yang, “A Novel Method of Score Level Fusion Using Multiple Impressions for Fingerprint Verification. SMC,” IEEE, pp. 5051-5056, 2009.
  27. A.K. Jain, A. Ross and S. Prabhakar, “A hybrid fingerprint matching using minutiae and texture features”, Proceedings of the International Conference on Image Processing (ICIP 2001), pp. 282–285
  28. C. Yang and J. Zhou. “A comparative study of combining multiple enrolled samples for fingerprint verification”. Pattern Recognition, vol.39, no. 11, pp. 2115-2130, 2006.
  29. D. Maltoni, D. Maio, A.K. Jain, and S. Prabhakar, “Handbook of Fingerprint Recognition,” Springer professional computing, Springer, 2009.
  30. Haiyun Xu, Raymond N.J. Veldhuis, Tom A.M. Kevenaar, Anton H.M. Akkermans, and Asker M. Bazen. Spectral minutiae: A fixed-length representation of a minutiae set. Computer Vision and Pattern Recognition Workshop, 0:16, 2008.
  31. D. Maio, D. Maltoni, J. L.Wayman, and A. K. Jain, “Fvc2000: Fingerprint verification competition,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 24, pp. 402-412, 2002.
  32. R. Cappelli, M. Ferrara, A. Franco and D. Maltoni, "Fingerprint verification competition 2006", Biometric Technology Today, vol.15, no.7-8, pp.7-9, August 2007.
  33. Arun A. Ross, Karthik Nandakumar, and Anil K. Jain. Handbook of Multibiometrics (International Series on Biometrics). Springer-Verlag New York, Inc., Secaucus, NJ, USA, 2006.
  34. S. Mazumdar and V. Dhulipala, “Biometric security using fingerprint recognition,” 3, 2008.
  35. H. Patel and P. Asrodia, “Fingerprint matching using two methods,” Vol. 2, No. 3, pp. 857-860, 2012.
  36. S. Bana and D. Kaur, “Fingerprint recognition using image segmentation,” International Journal Of Advanced Engineering Sciences And Technologies, Vol. 5, pp. 012-023, 2011.
  37. Azzoubi, Einas Almarghni, And Rosziati Bint Ibrahim. "An Enhancement Algorithm Using Gabor Filter For Fingerprint Recognition." Journal of Theoretical and Applied Information Technology 74.3 (2015).
  38. Kulshrestha, Megha, V. K. Banga, and Sanjeev Kumar. "Finger Print Recognition: Survey of Minutiae and Gabor Filtering Approach." International Journal of Computer Applications 50.4 (2012).
  39. J.venkatesh A Study and Analysis of Gabor Filter and K-Nearest Neighbor Approach on Minutia Matching for Fingerprint Recognition Indian Journal of Applied Research, Vol.III, Issue.IX September 2013
  40. M. Haghighat, S. Zonouz, M. Abdel-Mottaleb, "CloudID: Trustworthy cloud-based and cross-enterprise biometric identification," Expert Systems with Applications, vol. 42, no. 21, pp. 7905-7916, 2015.
  41. Kaggwa, F.; Ngubiri, J.; Tushabe, F., "Evaluation of multiple enrollment for fingerprint recognition," Computer & Information Technology (GSCIT), 2014 Global Summit on , vol., no., pp.1,6, 14-16 June 2014
  42. Kaggwa, F.; Ngubiri, J.; Tushabe, F. (2015, Mar.). Multiple enrollment based Fingerprint Recognition Systems: State of the Art Survey. IJCIT Volume 04-Issue 02 [Online]. Available:
  43. Kaggwa, F., Ngubiri, J. and Tushabe, F., 2015, June. Improving recognition performance in multiple enrollment based fingerprint recognition systems. In Computer & Information Technology (GSCIT), 2015 Global Summit on (pp. 1-5). IEEE.
  44. A. K. Jain, S. Prabhakar, L. Hong and S. Pankanti, "Filterbank-based fingerprint matching," in IEEE Transactions on Image Processing, vol. 9, no. 5, pp. 846-859, May 2000.
Index Terms

Computer Science
Information Sciences


Multiple enrollment Gabor Filter-based matching Spectral Minutiae-based matching Recognition performance memory consumption matching speed.