Abstract
Fuzzy models, traditionally used in the control field to model controllers or plants behavior, are used in this work to describe fingerprint images. The textures, in this case the directions of the fingerprint ridges, are described for the whole image by fuzzy if-then rules whose antecedents consider a part of the image and the consequent is the associated dominant texture. This low-level fuzzy model allows extracting higher-level information about the fingerprint, such as the existence of singular points and their fuzzy position within the image. This is exploited in two applications: to provide comprehensive information for users of unattended automatic recognition systems and to extract linguistic patterns to classify fingerprints.
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References
FVC database, http://bias.csr.unibo.it/fvc2002/
Maltoni, D., Maio, D., Jain, A.K., Prabhakar, S.: Handbook of Fingerprint Recognition, 2nd edn. Springer, Heidelberg (2009)
Bansal, R., Arora, P., Gaur, M., Sehgal, P., Bedi, P.: Fingerprint Image Enhancement using Type-2 Fuzzy Sets. In: Proc. Sixth Int. Conf. on Fuzzy Systems and Knowledge Discovery, Tianji, pp. 412–417 (2009)
Sagar, V.K., Alex, K.J.B.: Hybrid Fuzzy Logic and Neural Network Model for Fingerprint Minutiae Extraction. In: International Joint Conference on Neural Networks, Washington, pp. 3255–3259 (1999)
Vert, G., Nasser, S.: Minutia Verification using Fuzzy Logic and Geographic Points of Reference. In: The 14th IEEE Int. Conf. on Fuzzy Systems, Reno, pp. 839–844 (2005)
Yuan, L.: Application of Fuzzy Pattern Recognition on Fingerprint Processing. In: Second International Conference on Intelligent Computation Technology and Automation, Changsha, pp. 660–663 (2009)
Chen, X., Tian, J., Yang, X.: A New Algorithm for Distorted Fingerprints Matching Based on Normalized Fuzzy Similarity Measure. IEEE Trans. on Image Processing, 767–776 (2006)
Conti, V., Perconti, D., Romano, S., Tona, G., Vitabile, S., Ganglio, S., Sorbello, F.: Fast Fingerprint Classification Only Using the Directional Image. Knowledge-Based Intelligent Information and Engineering Systems. In: Apolloni, B., Howlett, R.J., Jain, L. (eds.) KES 2007, Part I. LNCS (LNAI), vol. 4692, pp. 34–41. Springer, Heidelberg (2007)
Xfuzzy Web page, http://www.imse-cnm.csic.es/Xfuzzy/
Kosko, B.: Fuzzy Systems as Universal Approximators. IEEE Transactions on Computers 43(11), 1329–1333 (1994)
Nachtegael, M., Van der Weken, D., Kerre, E.E.: Soft Computing Image Processing: Recent Advances. Series Studies in Fuzziness and Soft Computing, vol. 210. Springer, Heidelberg (2007)
Baturone, I., Gersnoviez, A.: Automatic Extraction of Linguistic Models for Image Description. In: IEEE International Conference on Fuzzy Systems. IEEE Computational Intelligence Society, Barcelona (2010)
Code for directional image, http://www.csse.uwa.edu.au/~pk/Research/MatlabFns/index.html
Baturone, I., Moreno-Velo, F.J., Gersnoviez, A.: A CAD Approach to Simplify Fuzzy System Descriptions. In: International Conference on Fuzzy Systems, Vancouver, pp. 2392–2399 (2006)
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Arjona, R., Gersnoviez, A., Baturone, I. (2011). Fuzzy Models for Fingerprint Description. In: Fanelli, A.M., Pedrycz, W., Petrosino, A. (eds) Fuzzy Logic and Applications. WILF 2011. Lecture Notes in Computer Science(), vol 6857. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23713-3_29
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DOI: https://doi.org/10.1007/978-3-642-23713-3_29
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