Ching-Tang Hsieh This email address is being protected from spambots. You need JavaScript enabled to view it.1, Shys-Rong Shyu1 and Kuo-Ming Hung1,2

1Department of Electrical Engineering, Tamkang University, Tamsui, Taiwan 251, R.O.C.
2Department of Information Management, Kainan University, Taipei, Taiwan, R.O.C.


 

Received: March 12, 2007
Accepted: April 28, 2008
Publication Date: June 1, 2009

Download Citation: ||https://doi.org/10.6180/jase.2009.12.2.09  


ABSTRACT


In this paper, we present a fast and precise method for fingerprint classification. The proposed method directly extracts the directional information from the thinned image of the fingerprint. We use an octagon mask to search the center point of the region of interest and consider both the direction information and the singular points in the region of interest to classify the fingerprints. In the system, not only is the amount of computation reduced but also can the extracted information be used for identification on AFIS. The system has been tested all 4000 fingerprint images on the NIST special fingerprint database 4. The classification accuracy reaches 93.425% with no rejection for 4-class classification problem.


Keywords: Biometrics, Fingerprint Classification, Wavelets, Poincare Index, Singular Point Detection


REFERENCES


  1. [1] Jain, L. C., Halici, U., Hayashi, I., Lee, S. B. and Tsutsui, S., Intelligent Biometric Techniques in Fingerprint and Face Recognition CRC Press, Boca Raton, FL, pp. 355398 (1999).
  2. [2] Henry, E. R., Classification and Uses of Finger Prints, London: Routledge (1900).
  3. [3] Karu, K. and Jain, A. K., “Fingerprint Classification,” Pattern Recognition, Vol. 29, pp. 389404 (1996).
  4. [4] Jain, A. K., Prabhakar, S. and Hong, L., “A multichannel Approach to Fingerprint Classification,” Pattern Analysis and Machine Intelligence, IEEE Transactions, Vol. 21, pp. 348359 (1999).
  5. [5] Meltem, B., Sakaraya, F. A. and Evans, B. L., “A Fingerprint Classification Technique Using Directional Image,” IEEE Asilomar Conf. on Signals Systems and Computers (1998).
  6. [6] Kawagoe, M. and Tojo, A., “Fingerprint Pattern Classification,” Pattern Recognition, Vol. 17, pp. 295303 (1984).
  7. [7] Wilson, C. L., Candela, G. T. and Watson, C. I., “Neural Network Fingerprint Classification,” J. Artificial Neural Networks, Vol. 1, pp. 203228 (1993).
  8. [8] Watson, C. I. and Wilson, C. L., “NIST Special Database 4, Fingerprint Database,” Nat’l Inst. of Standards and Technology, Mar. (1992).
  9. [9] Candela, G. T., Grother, P. J., Watson, C. I., Wilkinson, R. A. and Wilson, C. L., “PCASYS-a Pattern-Level Classification Automation System for Fingerprints,” Technical Report NISTIR 5647, Apr. (1995).
  10. [10] Senior, A., “A Hidden Markov Model Fingerprint Classifier,” Proc. 31st Asilomar Conf. Singals, Systems and Computers, pp. 306310 (1997).
  11. [11] Hsieh, C. T., Lai, E. and Wang, Y. C, “An Effective Algorithm for Fingerprint Image Enhancement Based on Wavelet Transform,” Pattern Recognition, Vol. 36, pp. 303312 (2003).
  12. [12] Daubechies, I., “The Wavelet Transform, Time  Frequency Localization and Signal Analysis,” IEEE Trans. Inf. Theory, Vol. 36, pp. 9611005 (1990).
  13. [13] Zhou, R. W., Quek, C. and NG, G. S., “Novel SinglePass Thinning Algorithm,” Pattern Recognition Letter, Vol. 16, pp. 12671275 (1995).
  14. [14] Wang, S., Zhang, W. W. and Wang, Y. S., “Fingerprint Classification by Directional Fields,” Proceedings of the Fourth IEEE International Conference on Multimodal Interfaces. (ICMI’2002), p. 395 (2002).
  15. [15] Sha, L., Zhao, F. and Tang, X., “Improved Fingercode for Filterbank-Based Fingerprint Matching,” in Proc. of IEEE International Conference on Image Processing (ICIP), Barcelona, Spain, pp. 895898 (2003).
  16. [16] Rusyn, B. and Ostap, O., “Estimation of Singular Points in Fingerprints Image,” TCSET’2002, Ukraine, Feb. 1823, p. 236 (2002).
  17. [17] Zhang, Q. and Yan, H., “Fingerprint Classification Based on Extraction and Analysis of Singularities and Pseudo Ridge,” Pattern Recognition, Vol. 37, pp. 22332243 (2004).