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Knuckle based human recognition
Języki publikacji
Abstrakty
W artykule przedstawiono propozycję metod oraz systemu rozpoznawania osób na podstawie kostek dłoni. W artykule zaproponowano wykorzystanie cech tekstury obliczonych w obrazie kostek dłoni. Zaproponowano metodologię, której początkowym etapem jest przetwarzanie wstępne obrazu oraz wykrycie linii. Następnie w celu obliczania cech zaproponowano wykorzystanie PHT (Probabilistic Hough Transform) oraz SURF (Speeded Up Robust Features). W artykule przedstawiono także trójstopniowy sposób porównywania cech oraz wyniki eksperymentów.
In this paper we present human identification method based on knuckle biometrics. Knuckle is a part of hand, and therefore, is easily accessible, invariant to emotions and other behavioral aspects (e.g. tiredness) and most importantly is rich in texture features which usually are very distinctive. The major contribution of this paper are texture-based knuckle features and their evaluation using benchmark knuckle image databases. We use PHT (Probabilistic Hough Transform) and SURF (Speeded Up Robust Features) features as well as the 3-step classification methodology. We prove the efficiency of the presented methods by reporting promising results.
Wydawca
Rocznik
Tom
Strony
92--95
Opis fizyczny
Bibliogr. 15 poz., tab., wykr.
Twórcy
autor
autor
autor
- Uniwersytet Technologiczno-Przyrodniczy w Bydgoszczy, Instytut Telekomunikacji
Bibliografia
- [1] Morales A., Ferrer M. A., Travieso C. M., Alonso J. B.: A knuckles texture verification method in a transformed domain. In: Proc. of 1st Spanish Workshop on Biometrics (on CD), Girona, Spain, 2007.
- [2] Kumar A., Zhou Y.: Human Identification using Knuckle Codes. Proc. BTAS, 2009.
- [3] Kumar A., Ravikanth Ch.: Personal authentication using finger knuckle surface. IEEE Trans. Information Forensics and Security, vol. 4, no. 1, pp. 98-110, 2009.
- [4] Kumar A., Zhou Y.: Personal identification using finger knuckle orientation features. Electronics Letters, vol. 45, no. 20, Sep. 2009.
- [5] Zhang L., Zhang L., Zhang D., Hailong Zhu H.: Online Finger-Knuckle-Print Verification for Personal Authentication. Pattern Recognition, vol. 43, no. 7, pp. 2560-2571, July 2010.
- [6] Zhang L., Zhang L., Zhang D.: Finger-knuckle-print verification based on band-limited phase-only correlation. Proceedings of the 13th International Conference on Computer Analysis of Images and Patterns, pp. 141-148, 2009.
- [7] http://www4.comp.polyu.edu.hk/~biometrics/FKP.htm
- [8] http://www4.comp.polvu.edu.hk/~csajavkr/mvhome/database request/knuckle/
- [9] Matas J., Galambos C., Kittler J. V.: Robust Detection of Lines Using the Progressive Probabilistic Hough Transform. CVIU(78), No. 1, April 2000, pp. 119-137.
- [10] Viola P., Jones M.: Rapid object detection using a boosted cascade of simple features. Computer Vision and Pattern Recognition, 2001. CVPR 2001 .Proceedings of the 2001 IEEE Computer Society Conference on, Volume: 1, pp. 511-518, 2001.
- [11] Bay H., Tuytelaars T., and Van Gool L.: Surf: Speeded up robust features. European Conference on Computer Vision, 1:404-417, 2006.
- [12] Choraś M., Kozik R.: Knuckle Biometrics for Human Identification. In: Choraś (Ed.): Image Processing and Communication Challenges 2, Advances in Soft Computing, 95-102, Springer, 2010.
- [13] Choraś M., Kozik R.: Feature Extraction Method for Contactless Palmprint Biometrics. In D.-S. Huang et al. (Eds.): Advanced Intelligent Computing Theories and Applications, Communications in Computer and Information Science 93, pp. 435-442, Springer, 2010.
- [14] Si-Yu Guo, Ya-Guang Kong, Qiu Tang, Fan Zhang: Probabilistic Hough transform for line detection utilizing surround suppression. Machine Learning and Cybernetics, 2008 International Conference on, vol.5, no., pp. 2993-2998, 12-15 July 2008.
- [15] Galambos C., Kittler J., Matas J.: Gradient based progressive probabilistic Hough transform. Vision, Image and Signal Processing, IEE Proceedings, vol.148, no.3, pp.158-165, Jun 2001.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BWAN-0008-0025