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New methods to determine similarity of signatures based on local extremes

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Authentication based on handwritten signature is one of the most accepted authentication systems based on biometry. In this paper a method for the automatic verification of on-line handwritten signatures using three similarity measures is described. The proposed approach, is based on extreme values and dynamic features of the signature. In investigations proposed coefficients together with the factor [R2] were connected and new signature recognition quality has been achieved.
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Bibliogr. 10 poz., rys., tab.
  • University of Silesia. Institute of Informatics, 41-200 Sosnowiec, Będzińska 39, Poland
  • [1] HUANG B.Q., KECHADI M-T., A Fast Feature Selection Model for Online Handwriting Symbol Recognition, Proceedings of the 5th International Conference on Machine Learning and Applications (ICMLA'06), 2006.
  • [2] ASIF MASOOD1 SHAIQ A., Role of Corner Detection in Capturing Shape Outlines, 7th International Conference on Computer Vision, Pattern Recognition and Image Processing.
  • [3] FENG H., CHOONG WAH CH.., Online signature verification using a new extreme points warping technique, Pattern Recognition Letters archive Volume 24 , Issue 16 (December 2003), pp 2943-2951, 2003 .
  • [4] 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, ISSN 1755-8301, pp. 47-62.
  • [5] 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), Ełk. 2007, pp. 282-287.
  • [6] HANSHENG L., SRINIVAS P., VENU G., ER2: An Intuitive Similarity Measure for On-Line Signature Verification, Proceedings of the Ninth International Workshop on Frontiers in Handwriting Recognition, pp. 191–195, 2004.
  • [7] BILLINGS S., LEE S., Nonlinear Fisher discriminant analysis using a minimum squared error cost function and the orthogonal least squares algorithm, 2002 Elsevier Science, pp. 263-270.
  • [8] AL-SHOSHAN, A.I, Handwritten Signature Verification Using Image Invariants and Dynamic Features, Computer Graphics, Imaging and Visualisation, International Conference on Publication, 2006, pp. 173-176.
  • [9] PIYUSH SHANKERA A., RAJAGOPALAN A.N., Off-line signature verification using DTW, Image Processing and Computer Vision Lab, Department of Electrical Engineering, Indian Institute of Technology Madras, India 2006
  • [10] GUPTAA G.K., JOYCEB R.C., Using position extreme points to capture shape in on-line handwritten signature verification, Faculty of Information Technology, 2006.
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