PL EN


Preferencje help
Widoczny [Schowaj] Abstrakt
Liczba wyników
Tytuł artykułu

Signatures recognition method by using the normalized Levenshtein distances

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
This study examines the effectiveness of normalized Levenshtein metrics in the process of recognition of handwritten signatures. Three methods of normalization of the Levenshtein metric were taken into consideration. In addition, it was determined, which signature features are most important during their comparisons with the use of the aforementioned metric. The following signature features were examined: coordinates of signature points, pen pressure in successive points, and different types of pen speed. The influence of individual parameters of the Levenshtein algorithm on the obtained results was also determined, and the best method of normalization was selected.
Rocznik
Tom
Strony
73--77
Opis fizyczny
Bibliogr. 11 poz., rys., tab.
Twórcy
autor
  • University of Silesia, Institute of Computer Science, 41-200 Sosnowiec, Będzińska 39, Poland
autor
autor
Bibliografia
  • [1] AL-SHOSHAN A.I., Handwritten Signature Verification Using Image Invariants and Dynamic Features, Computer Graphics, Imaging and Visualisation, International Conference on Volume, pp. 173 – 176, 2006.
  • [2] CHA S., Comprehensive Survey on Distance/Similarity Measures between Probability Density Functions, International Journal of Mathematical Models and Methods in Applied Sciences, vol. 1(4), pp. 300 – 307, 2007.
  • [3] DOROZ R., PORWIK P., PARA T., WRÓBEL K., Dynamic signature recognition based on velocity changes of some features, International Journal of Biometrics, Vol. 1, No. 1, pp. 47-62, 2008.
  • [4] IMPEDOVO S., PIRLO G., Verification of Handwritten Signatures: an Overview, 14th International Conference on Image Analysis and Processing (ICIAP’07), pp. 191-196, 2007.
  • [5] KHAN M. K., KHAN M. A., KHAN M.A.U., AHMAD I., On-Line Signature Verification by Exploiting Inter-Feature Dependencies, 18th International Conference on Pattern Recognition (ICPR’06), vol. 2, pp. 796 – 799, 2006.
  • [6] LEVENSHTEIN V.I., Binary codes capable of correcting deletions, insertions, and reversals, Soviet Physics Dokl., pp. 707-710, 1966.
  • [7] MARZAL A., VIDAL E., Computation of Normalized Edit Distance and Applications, IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 15, no. 9, pp. 926-932, 1993.
  • [8] PORWIK P., The Compact Three Stages Method of the Signature Recognition, Proceeding of 6th International Conference on Computer Information Systems and Industrial Management Applications (CISIM'07), pp. 282-287, 2007.
  • [9] WEIGEL A., FEIN F., Normalizing the Weighted Edit Distance, Proc. 12th IAPR Int’l Conf. Pattern Recognition, vol.2, Conf. B: Computer Vision and Image Processing, pp. 399-402, 1994.
  • [10] WROBEL K., DOROZ R., The new method of signature recognition based on least squares contour alignment, International Multi- Conference on Biometrics and Kansei Engineering (ICBAKE’09), pp. 80-83, 2009.
  • [11] YUJIAN L., BO L., A Normalized Levenshtein Distance Metric, IEEE Trans. on Pattern Analysis and Machine Intelligence, vol. 26, no. 6, pp. 1091-1095, 2007.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-PWA4-0002-0014
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.