Effectiveness of Extended Invariant Moments in Fingerprint Analysis

Authors

  • Hussein Atiya Lafta iraq,babylon,University of babylon
  • Safa Saad Abbas

Keywords:

Biometrics, Pattern Recognition, invariant moments, Fingerprint, Authentication, Identification, K_NN

Abstract

Automatic fingerprint identification system includes person identification process based on fingerprint which is in digital form. Fingerprint identification system consists of acquiring fingerprint module, classification module, and the matching module, which it performs a comparison between the unknown input fingerprint and the others stored in the fingerprint database and related to the class labeled by the classification module. In this paper, extended are used in fingerprint analyzing process for extracting local features. In extraction local features, extended moments gave best results than when using centralized invariant moments with order 3. for decision making in identification, K_NN classifier used in this work.

References

Acharya T., and Ray A. K., "Image Processing: Principles And Applications", Wiley-Interscience, USA, 2005.

Afsar F. A., Arif M., and Hussain M., "Fingerprint Identification and Verification System Using

Minutiae Matching", National Conference or Emerging Technologies, 2004.

Al-Kharaz A. A. M., "Fingerprints Recognition Using Gabor Filters", MSC. Thesis, Baghdad University, 2005.

Bhuyan M. H., and Bhattacharyya D. K., "An Effective Fingerprint Classification And Search

Method", International Journal Of Computer Science And Network Security, Vol.9, No.11, November 2009.

Bow S., "Pattern Recognition And Image Processing", Marcel Dekker, New York, USA, 2002.

Cappelli R., Maltoni D., and Turroni F., "Benchmarking Local Orientation Extraction in

Fingerprint Recognition", IEEE International Conference on Pattern Recognition, 2010.

Dass S. C., Zhu Y., and Jain A. K., "Validating a Biometric Authentication System: Sample Size

Requirements", IEEE Transaction on Pattern Analysis and Machine Intelligence, Vol.28, No.12, Dec. 2006.

Espinosa V., "Minutiae Detection Algorithm For Fingerprint Recognition", IEEE, 2002.

He M., and Zhao H., "An Identity Authentication Based on Fingerprint Identification", Proceeding

of the 2009 International Symposium on Web Information Systems And Applications, pp.261-263, May 2009.

Jain A. K., Flynn P., and Ross A. A., "Handbook of Biometrics", Springer, 2008.

Konar A., "Artificial Intelligence And Soft Computing", USA, 2000.

Lee H. C., and Gaensslen R. E., "Advances In Fingerprint Technology", Second Edition, CRC,

USA, 2001.

Li Y., "Reforming The Theory Of Invariant Moments For Pattern Recognition", Pattern Recognition

Lett., Vol.25, pp.723-730, July 1992.

Mostafa M., "A Novel Line Pattern Algorithm for Embedded Fingerprint Authentication

System", GVIP Special issue on Fingerprint Recognition, 2007.

Nixon M. S., and Aguado A. S., "Feature Extraction And Image Processing", Newnes, Great

Britain, 2002.

Pankanti S., Bolle R. M., and Jain A., "Biometrics: The Future Of Identification", Computer,

Vol.33, No.2, pp.46-49, Feb.9, 2000.

Ratha N., and Bolle R., "Automatic Fingerprint Recognition Systems", Springer, New York,

Ratha N., and Govindaraju V., "Advances In Biometrics", Springer, 2008.

Ravi J., Raja K. B., and Venugopal K. R., "Fingerprint Recognition Using Minutiae Score

Matching", International Journal Of Engineering Science And Technology, Vol.1(2), pp.35-42, 2009.

Reid P., "Biometrics For Network Security", Prentice Hall, Dec.30, 2003.

Ritter G. X., and Wilson J. N., "Handbook Of Computer Vision Algorithms In Image Algebra",IT Knowledge, 1996.

Simon D., Ortega J., Cruz S., and Etal, "Minutiae Extraction Scheme for Fingerprint

Recognition System", IEEE, pp.254-257, 2001.

Thai L. H., and Tam H. N., "Fingerprint Recognition Using Standardized Fingerprint Model",

International Journal Of Computer Science Issues, Vol.7, Issue 3, No.7, May 2010.

Uludag U., and Jain A., "Securing Fingerprint Template: Fuzzy Vault with Helper Data",

Proceedings of the 2006 Conference on Computer Vision and Pattern Recognition Workshop, IEEE, 2006.

Wahab A., Chin S. H., and Tan E. C., "Novel Approach To Automated Fingerprint

Recognition", IEE Proceeding-Vis. Image Signal Process, Vol.145, No.3, June 1998.

Downloads

Published

2013-10-14

How to Cite

Lafta, H. A., & Abbas, S. S. (2013). Effectiveness of Extended Invariant Moments in Fingerprint Analysis. Asian Journal of Computer and Information Systems, 1(3). Retrieved from https://ajouronline.com/index.php/AJCIS/article/view/360