Abstract
Most fingerprint recognition techniques are based on minutiae matching and have been well studied. However, this technology still suffers from problems associated with the handling of poor quality impressions. One problem besetting fingerprint matching is distortion. Distortion changes both geometric position and orientation, and leads to difficulties in establishing a match among multiple impressions acquired from the same finger tip. In this paper, according to the particularity of fingerprint distortion, we propose a combined radial basis function (RBF) model, which separately builds rigid and nonrigid transformations, for attacking the distortion problem. Combined RBF model provides more accurate mapping function between a possible matched-pair. Experiments on real data demonstrate the efficacy of the proposed method in improving the compensation of fingerprint distortion.
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References
Arad, N., Reisfeld, D.: Image warping using few anchor points and radial functions. Computer Graphics Forum 14(1), 35–46 (1995)
Bazen, A.M., Gerez, S.H.: Elastic mniutiae matching by means of thin-plate spline models. Pattern Recognition 36(8), 1859–1867 (2003)
Bebis, G., Deaconu, T., Georgiopoulos, M.: Fingerprint identification using delaunay triangulation, pp. 452–459 (1999)
Bhanu, B., Tan, X.J.: Fingerprint indexing based on novel features of minutiae triplets. IEEE Trans. on PAMI 25(5), 616–622 (2003)
Cappelli, R., Maio, D., Maltoni, D.: Modelling plastic distortion in fingerprint images. In: Singh, S., Murshed, N., Kropatsch, W.G. (eds.) ICAPR 2001. LNCS, vol. 2013, pp. 369–376. Springer, Heidelberg (2001)
Farina, A., Kovács-Vajna, Z.M., Leone, A.: Fingerprint minutiae extraction from skeletonized binary images. Pattern Recognition 32, 877–889 (1999)
Galton, F.: Fingerprints. Macmillan, London (1892)
Jain, A.K., Hong, L., Bolle, R.M.: On-line fingerprint verification. IEEE Trans. on PAMI 19(4), 302–313 (1997)
Liang, X.F.: Fingerprint image analysis using computational geometric techniques, Ph.D. thesis. Japan Advanced Institute of Science and Technology, 68–72 (2005)
Luo, X., Tian, J., Wu, Y.: A minutia matching algorithm in fingerprint verification. In: Proc. of ICPR, vol. 4, pp. 833–836 (2000)
Parziale, G., Niel, A.: A fingerprint matching using minutiae triangulation. In: Zhang, D., Jain, A.K. (eds.) ICBA 2004. LNCS, vol. 3072, pp. 241–248. Springer, Heidelberg (2004)
Ross, A., Dass, S.C., Jain, A.K.: Estimating fingerprint deformation. In: Zhang, D., Jain, A.K. (eds.) ICBA 2004. LNCS, vol. 3072, pp. 249–255. Springer, Heidelberg (2004)
Ruprecht, D., Müller, H.: Image warping with scattered data interpolation. IEEE Computer Graphics and Applications 15(2), 37–43 (1995)
Senior, A., Bolle, R.: Improved fingerprint matching by distortion removal. IEICE Trans. on INF. & SYST. E84-D(7), 825–832 (2001)
Kovács-Vajna, Z.M.: A fingerprint verification system based on triangular matching and dynamic time warping. IEEE Trans. on PAMI 22(11), 1266–1276 (2000)
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© 2006 Springer-Verlag Berlin Heidelberg
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Liang, X., Asano, T., Zhang, H. (2006). A Combined Radial Basis Function Model for Fingerprint Distortion. In: Campilho, A., Kamel, M. (eds) Image Analysis and Recognition. ICIAR 2006. Lecture Notes in Computer Science, vol 4142. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11867661_26
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DOI: https://doi.org/10.1007/11867661_26
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-44894-5
Online ISBN: 978-3-540-44896-9
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