Citation

Krishna Madasu, Vamsi and Mohd. Hafizuddin Mohd. Yusof, K and Hanmandlu, Madasu and Kubik, Kurt (2003) Off-line signature verification and forgery detection system based on fuzzy modeling. In: AI 2003: Advances in Artificial Intelligence. Lecture Notes in Computer Science, 2903 (2903). Springer Berlin Heidelberg, pp. 1003-1013. ISBN 978-3-540-20646-0

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Abstract

This paper presents an innovative approach for signature verification and forgery detection based on fuzzy modeling. The signature image is binarized and resized to a fixed size window and is then thinned. The thinned image is then partitioned into a fixed number of eight sub-images called boxes. This partition is done using the horizontal density approximation approach. Each sub-image is then further resized and again partitioned into twelve further sub-images using the uniform partitioning approach. The features of consideration are normalized vector angle (a) from each box. Each feature extracted from sample signatures gives rise to a fuzzy set. Since the choice of a proper fuzzification function is crucial for verification, we have devised a new fuzzification function with structural parameters, which is able to adapt to the variations in fuzzy sets. This function is employed to develop a complete forgery detection and verification system.

Item Type:	Book Section
Additional Information:	Proceedings 16th Australian Conference on AI, Perth, Australia, December 3-5, 2003.
Subjects:	Q Science > QA Mathematics > QA71-90 Instruments and machines > QA75.5-76.95 Electronic computers. Computer science
Divisions:	Faculty of Computing and Informatics (FCI)
Depositing User:	Ms Rosnani Abd Wahab
Date Deposited:	24 Aug 2011 00:10
Last Modified:	23 Dec 2013 03:54
URII:	http://shdl.mmu.edu.my/id/eprint/2598

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