Abstract
Law enforcement, border security and forensic applications are some of the areas where fingerprint classification plays an important role. A new technique based on wave atoms decomposition and bidirectional two-dimensional principal component analysis (B2DPCA) using extreme learning machine (ELM) for fast and accurate fingerprint image classification is proposed. The foremost contribution of this paper is application of two dimensional wave atoms decomposition on original fingerprint images to obtain sparse and efficient coefficients. Secondly, distinctive feature sets are extracted through dimensionality reduction using B2DPCA. ELM eliminates limitations of classical training paradigm; trains data at a considerably faster speed due to its simplified structure and efficient processing. Our algorithm combines optimization of B2DPCA and the speed of ELM to obtain a superior and efficient algorithm for fingerprint classification. Experimental results on twelve distinct fingerprint datasets validate the superiority of our proposed method.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Jain, A.K., Ross, A., Pankanti, S.: Biometrics: A tool for information security. IEEE Transaction on Information Forensics Security 1(2), 125–143 (2006)
Maltoni, D., Maio, D., Jain, A.K., Prabhakar, S.: Handbook of fingerprint recognition. Springer, New York (2003)
Yager, N., Amin, A.: Fingerprint classification: a review. Pattern Analysis and Applications 7(1), 77–93 (2004)
Jain, A., Chen, Y., Demitrius, M.: Pores and Ridges: Fingerprint matching using Level 3 features. In: Proc. 18th International Conference on Pattern Recognition, vol. 4, pp. 477–480 (2006)
Maio, D., Maltoni, D., Cappelli, R., Wayman, J., Jain, A.K.: FVC 2004: Third fingerprint verification competition. In: Zhang, D., Jain, A.K. (eds.) ICBA 2004. LNCS, vol. 3072, pp. 1–7. Springer, Heidelberg (2004)
Bazen, A., Gerez, S.: Systematic methods for the computation of the direction fields and singular points of fingerprints. IEEE Transaction on Pattern Analysis and Machine Intelligence 24(7), 905–919 (2002)
Bhanu, B., Tan, X.: Fingerprint indexing based on novel features of minutiae triplets. IEEE Transactions on Pattern Analysis and Machine Intelligence 25(5), 616–622 (2003)
Fitz, A., Green, R.: Fingerprint classification using a hexagonal fast Fourier transform. Pattern Recognition 29(10), 1587–1597 (1996)
Seokwon, L., Boohee, N.: Fingerprint Recognition using Wavelet Transform and Probabilistic Neural Network. In: Proc. of International Joint Conference on Neural Networks, vol. 5, pp. 3276–3279 (1999)
Wilson, C., Candela, G., Grother, P., Watson, C., Wilkinson, R.: Massively parallel neural network fingerprint classification system. National Institute of Standards and Technology; NISTIR 4880 (1992)
Luo, J., Lin, S., Lei, M., Ni, J.: Application of dimensionality reduction analysis to fingerprint recognition. In: ISCID, vol. 2, pp. 102–105 (2008)
Demanet, L., Ying, L.: Wave Atoms and Sparsity of Oscillatory Patterns. Applied and Computational Harmonic Analysis 23(3), 368–387 (2007)
Yang, J., Zhang, D., Frangi, A., Yang, J.: Two-dimensional PCA: a new approach to appearance based face representation and recognition. IEEE Transaction on Pattern Analysis and Machine Intelligence 26(1), 131–137 (2004)
Zhang, D., Zhou, Z.: (2D)2 PCA: Two-directional two-dimensional PCA for efficient face representation and recognition. Neurocomputing 69(1), 224–231 (2005)
Pankanti, S., Prabhakar, S., Jain, A.K.: On the Individuality of Fingerprints. IEEE Transactions on Pattern Analysis and Machine Intelligence 24(8), 1010–1025 (2002)
Huang, G., Zhu, Q., Siew, C.: Extreme learning machine: Theory and applications. Neurocomputing 70(1), 489–501 (2006)
Ross, A., Jain, A.K., Reisman, J.: A Hybrid Fingerprint Matcher. Pattern Recognition 36(7), 1661–1673 (2003)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Mohammed, A.A., Jonathan Wu, Q.M., Sid-Ahmed, M.A. (2010). Application of Wave Atoms Decomposition and Extreme Learning Machine for Fingerprint Classification. In: Campilho, A., Kamel, M. (eds) Image Analysis and Recognition. ICIAR 2010. Lecture Notes in Computer Science, vol 6112. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13775-4_25
Download citation
DOI: https://doi.org/10.1007/978-3-642-13775-4_25
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-13774-7
Online ISBN: 978-3-642-13775-4
eBook Packages: Computer ScienceComputer Science (R0)