Off-Line Signature Verification and Recognition

Authors

  • Vahe Khachaturyan Institute for Informatics and Automation Problems of NAS RA

Keywords:

Pattern Recognition, Signature Recognition, Image Morphology

Abstract

In this paper we propose a technique that can be used for signature recognition. This technique is a contour based technique. Here we propose a simple and effective approach that can be easily implemented in a programming language.
The paper deals with the recognition of the signature, as human operator generally makes the work of signature recognition. Hence the algorithm simulates human behavior, to achieve perfection and skill through AI. The logic that decides the extent of validity of the signature must implement Artificial Intelligence Pattern recognition is the science that concerns the description or classification of measurements, usually based on underlying model. Since most pattern recognition tasks are first done by humans and automated later, the most fruitful source of features has been to ask the people who classify the objects how they tell them a part. Signatures are a behavioral biometric that change over a period of time and are influenced by physical and emotional conditions of a subject. This technique gives acceptable results in a simple and fast way.

References

M. Sonka, V. Hlavac and R. Boyle, “Image processing analysis, and machine vision”,Thomson Learning, Singapore, pp. 563-64, 573, 583, 593, 2002.

S. Loncaric, A. Dhawan,” A morphological signature transform for Shape Description.”Pattern Recognition, 6: pp. 1029-1037. 1993.

Evett and R. N. Totty, ”Study of the variation in the dimensions of genuine signatures”,Journal of the Forensic Science Society, vol. 25, pp. 207-215, 1985

B. Fang, C. H. Leung, Y. Y. Tang, K. W. Tse, P. C. K. Kwok, Y. K. Wong,”Off-Linesignature verification by the tracking of feature and stroke positions”, Pattern Recognition, vol.36, pp. 91-101, 2003.

Y. Mizukami, H. Miike, M. Yoshimura, and I. Yoshimura, ”An Off-Line signatureverification system using an extracted displacement function”, In Proceedings of ICDAR, pp.757-760, 1999.

W. F. Nemcek and W. C. Lin, ”Experimental investigation of automatic signatureverification” IEEE Transactions on Systems, Man and Cybernetics, vol. 4 , pp. 121-126, 1974.

T. Joachims, “Text categorization with support vector machines: Learning with manyrelevant features”. Proceedings of the Tenth European Conference on Machine Learning. Berlin:Springer, pp. 137 -142, 1998.

Downloads

Published

2021-12-10

How to Cite

Khachaturyan, V. . (2021). Off-Line Signature Verification and Recognition. Mathematical Problems of Computer Science, 36, 115–120. Retrieved from http://mpcs.sci.am/index.php/mpcs/article/view/273