Abstract
This paper presents an improved image-based fingerprint verification system. The proposed system enhances an input fingerprint image using a contextual filtering technique in the frequency domain, and uses the complex fillers to identify the core point. Subsequently, a region of interest (ROI) of a predefined size, which is centered around the detected core point, is extracted. The resulting ROI is rotated based on the detected core point angle to ensure rotation invariance. The proposed system extracts the absolute average deviation from the outputs of eight oriented Gabor filters that are applied to the ROI. To reduce the dimensionality of the extracted features whilst generating more discriminatory representation, this paper compares the unsupervised principal component analysis and the supervised linear discriminant analysis methods for dimensionality reduction. User-specific thresholding schemes are investigated. The effectiveness of the proposed algorithm is evaluated on the public FVC2002 set_a database. Experimental results demonstrate the superiority of the introduced solution in comparison with existing approaches.
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
Ratha, N.K., Chen, S.Y., Jain, A.K.: Adaptive flow orientation-based feature-extraction in fingerprint images. Pattern Recognition 28(11), 1657–1672 (1995)
Jain, A.K., Hong, L., Bolle, R.M.: Real-time matching system for large fingerprint databases. IEEE Trans on Pattern Analysis and Machine Intelligence 19(4), 302–314 (1997)
Tico, M., Immomen, a.E., Ramo, P., Kuosmanen, P., Saarinen, J.: Fingerprint recognition using wavelet features. In: Proc. ISCAS, Australia, vol. 2, pp. 21–24 (May 2001)
Hung, D.C.D.: Enhancement and feature purification of fingerprint images. Pattern Recognition 26(11), 1661–1671 (1993)
Maltoni, D., Maio, D., Jain, A.K., Prabhakar, S.: Handbook of Fingerprint Recognition, 2nd edn. Springer, London (2009)
Khalil, M.S., Mohamad, D., Khan, M.K., Al-Nuzaili, Q.: Fingerprint pattern classification. Digital Signal Processing 20, 1264–1273 (2010)
Nanni, L., Lumini, A.: Descriptors for image-based fingerprint matcher. Expert Systems with Applications 36(10), 12414–12422 (2009)
Wang, C.J.L.S.D.: Fingerprint feature extraction using gabor filters. Electronic Letters 35(4), 288–290 (1999)
Jain, A.K., Prabharkar, S., Hong, L., Pankanti, S.: Filterbank-based fingeerprnt matching. IEEE Trans. on Image Processing 9, 846–859 (2000)
Jin, A.T.B., Ling, D.N.C., Song, O.T.: An efficient fingerprint verification system using integrated wavelet and fourier-mellin invariant transform. Image and Vision Computing 22(6), 503–513 (2004)
Hu, M.K.: Visual pattern recognition by moment invariants. IRE Transactions on Information Theory, 179–187 (1962)
Yang, J.C., Park, D.S.: A fingerprint verification algorithm using tessellated invariant moment features. Neurocomputing 71(10-12), 1939–1946 (2008)
Yang, J.C., Park, D.S.: Fingerprint verification based on invariant moment features and nonlinear bpnn. International Journal of Control, Automation, and Systems 6(6), 800–808 (2008)
Chikkerur, S., Cartwright, A.N., Govindaraju, V.: Fingerprint enhancement using stft analysis. Pattern Recognition 40(1), 198–211 (2007)
Nilsson, K., Bigun, J.: Complex filters applied to fingerprint images detecting prominent symmetry points used for alignment. In: Biometric Authentication, pp. 39–47 (2002)
Prabhakar, S.: Fingerprint Classification and Matching Using a Filterbank. PhD thesis, Michigan State University (2001)
Jolliffe, L.T.: Principle Component Analysis. Springer, New York (1986)
Belhumeur, P.N., Hespanha, J.P., Kriegman, D.J.: Eigenfaces vs. Fisherfaces: recognition using class specific linear projection. IEEE Transactions on PAMI 19(7), 711–720 (1997)
Ross, A., Jain, A.K., Reisman, J.: A hybrid fingerprint matcher. Pattern Recognition 36(7), 1661–1673 (2003)
Amornraksa, T., Tachaphetpiboon, S.: Fingerprint recognition using dct features. Electronics Letters 42(9), 522–523 (2006)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Ibrahim, M.T., Wang, Y., Guan, L., Venetsanopoulos, A.N. (2011). Fingerprint Verification Using Rotation Invariant Feature Codes. In: Kamel, M., Campilho, A. (eds) Image Analysis and Recognition. ICIAR 2011. Lecture Notes in Computer Science, vol 6754. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21596-4_12
Download citation
DOI: https://doi.org/10.1007/978-3-642-21596-4_12
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-21595-7
Online ISBN: 978-3-642-21596-4
eBook Packages: Computer ScienceComputer Science (R0)