Complex Filters Applied to Fingerprint Images Detecting Prominent Symmetry Points Used for Alignment
For the alignment of two fingerprints position of certain landmarks are needed. These should be automatically extracted with low misidentification rate. As landmarks we suggest the prominent symmetry points (core-points) in the fingerprint. They are extracted from the complex orientation field estimated from the global structure of the fingerprint, i.e. the overall pattern of the ridges and valleys. Complex filters, applied to the orientation field in multiple resolution scales, are used to detect the symmetry and the type of symmetry. Experimental results are reported.
KeywordsGlobal Structure Equal Error Rate Fingerprint Image Symmetry Detection Gaussian Pyramid
Unable to display preview. Download preview PDF.
- R. Capelli, A. Lumini, D. Maio, and D. Maltoni. Fingerprint classification by directional image partitioning. IEEE Transactions on Pattern Analysis and Machine Intelligence, 21(5):402–421, May 1999.Google Scholar
- J. Bigun and G. H. Granlund. Optimal orientation detection of linear symmetry. IEEE Computer Society Press, Washington, DC, pages 433–438, June 1987. In First International Conference on Computer Vision, ICCV (London).Google Scholar
- A. K. Jain, S. Prabhakar, L. Hong, and S. Pankanti. Filterbank-based fingerprint matching. IEEE Transactions on Image Processing, 9(5):846–859, May 2000.Google Scholar
- J. Van de Weijer, L. J. van Vliet, P. W. Verbeek, and M. van Ginkel. Curvature estimation in oriented patterns using curvlinear models applied to gradient vector fields. IEEE Transactions on Pattern Analysis and Machine Intelligence, 23(9):1035–1042, September 2001.Google Scholar
- M. K. Koo and A. Kot. Curvature-based singular points detection. Springer LNCS 2091, Bigun and Smeraldi Eds. Springer, 2001. Third International Conference AVBPA 2001, Halmstad, Sweden.Google Scholar
- J. Bigun. Recognition of local symmetries in gray value images by harmonic functions. Ninth International Conference on Pattern Recognition, Rome, pages 345–347, 1988.Google Scholar
- H. Knutsson, M. Hedlund, and G. H. Granlund. Apparatus for determining the degree of consistency of a feature in a region of an image that is divided into discrete picture elements. US. Patent, 4.747.152, 1988.Google Scholar
- J. Bigun. Pattern recognition in images by symmetries and coordinate transformations. Computer Vision and Image Understanding, 68(3):290–307, December 1997.Google Scholar
- J. Bigun and T. Bigun. Symmetry derivatives of gaussians illustrated by cross tracking. Research report IDE-0131, September 2001.Google Scholar
- B. Johansson. Multiscale curvature detection in computer vision. Tech. lic., Linkoping University, Linkoping University, Dep. Electrical Eng., SE-581 83, 2001.Google Scholar