FINGERPRINT IMAGE ENHANCEMENT USING MEDIAN SIGMOID FILTER

Authors

  • Ainul Azura Abdul Hamid ViCubeLab, Faculty of Computing, Universiti Teknologi Malaysia, 81310 UTM Johor Bahru, Johor, Malaysia
  • Rosely Kumoi ViCubeLab, Faculty of Computing, Universiti Teknologi Malaysia, 81310 UTM Johor Bahru, Johor, Malaysia
  • Mohd Shafry Mohd Rahim UTM-IRDA DMC, Universiti Teknologi Malaysia, 81310 UTM Johor Bahru, Johor, Malaysia
  • Nur Zuraifah Syazrah ViCubeLab, Faculty of Computing, Universiti Teknologi Malaysia, 81310 UTM Johor Bahru, Johor, Malaysia

DOI:

https://doi.org/10.11113/jt.v75.5057

Keywords:

Enhancement, filtering, median sigmoid, distance vector

Abstract

Quality of fingerprint image is most essential to ensure good performance of minutiae extraction result since it depends heavily on the quality of fingerprint images. Fingerprint image with noise usually will produce spurious minutiae. In this paper, new combination filter called Median Sigmoid (MS) filter is introduced to remove the unwanted noise created during the acquisition process and hence increasing the accuracy of minutiae extraction result. The result shows that MS filter is an effective filter in enhancing the quality of a noisy image.

References

Bhowmik, P., et al. 2012. Fingerprint Image Enhancement and Its Feature Extraction for Recognition. International Journal of Scientific and Technology Research (IJSTR). 1(5): 117-121.

Asif, I. K. and Arif, M. W. 2014. Strategy to Extract Reliable Minutiae Points for Fingerprint Recognition. IEEE International Advance Computing Conference (IACC). 1071-1075.

Gupta, A. and Kaushik, Y. 2014. Comparative Study of Noise Removal Techniques. International Journal of Current Engineering and Technology. 4(6): 3904-3907.

Kumar, J. and Abhilasha. 2014. Survey on Non Linear Noise Removal Techniques for Salt Pepper Noise in Digital Images. An International Journal of Engineering Sciences. 3(2014): 90-95.

Moorthy, M.S., Jayaraj, R., and Jagadeesan, J. 2014. Fingerprint Authentication System using Minutiae Matching and Application. International Journal of Computer Science and Mobile Computing (IJCSMC). 3(3): 616-622.

Babatunde, I. G., Charles, A., and Olatunbosun, O. 2013. Uniformity Level Approach to Fingerprint Ridge Frequency Estimation. International Journal of Computer Applications. 61(22): 26-32.

Misra, D .K. and Tripathi, S. P. 2012. A Study Report on Finger Print Image Enhancement Methods. International Journal of Computer Science and Communication. 3(1): 163-170.

Watson, C. I. and Wilson, C. L. 1992. NIST Special Database 4. Database: National Institute of Standards and Technology. [Internet] From: http://www.nist.gov/srd/nistsd4.cfm.

Watson, C. I. 1993. NIST Special Database 14, Mated Fingerprint Card Pairs 2 (MFCP2). Database: National Institute of Standards and Technology [Internet] From: http://www.nist.gov/srd/nistsd14.cfm.

Maltoni, D., Maio, D., Jain, A. K., and Prabhakar, S. 2009. Handbook of Fingerprint Recognition. 2nd ed. New York: Springer. 59-74.

Kanan, P., Deepa, S., and Ramakrishnan, R. 2012. Contrast Enhancement of Sports Images using Two Comparative Approaches. American Journal of Intelligent Systems. 2(6): 141-147.

Hassan, N. and Akamatsu, N. 2004. A New Approach for Contrast Enhancement using Sigmoid Function. The International Arab Journal of Information Technology. 1(2): 221-226.

Balaji, S. and Venkatram, N. 2008. Filtering of Noise in Fingerprint Images. International Journal of Systems and Technologies. 1(1): 87-94.

Downloads

Published

2015-07-29

Issue

Section

Science and Engineering

How to Cite

FINGERPRINT IMAGE ENHANCEMENT USING MEDIAN SIGMOID FILTER. (2015). Jurnal Teknologi, 75(4). https://doi.org/10.11113/jt.v75.5057