Off-line signature verification and forgery detection system based on fuzzy modeling

Madasu, V., Yusof, M., Hanmandlu, M. and Kubik, K. K. T. (2003). Off-line signature verification and forgery detection system based on fuzzy modeling. In: T. Gideon and L. Fung, AI2003: Advances in Artificial Intelligence. The Sixteenth Australian Conference on Artificial Intelligence, Perth, Australia, (1003-1013). 10-12 December 2003. doi:10.1007/b94701


Author Madasu, V.
Yusof, M.
Hanmandlu, M.
Kubik, K. K. T.
Title of paper Off-line signature verification and forgery detection system based on fuzzy modeling
Conference name The Sixteenth Australian Conference on Artificial Intelligence
Conference location Perth, Australia
Conference dates 10-12 December 2003
Proceedings title AI2003: Advances in Artificial Intelligence   Check publisher's open access policy
Journal name Ai 2003: Advances in Artificial Intelligence   Check publisher's open access policy
Place of Publication Berlin, Germany
Publisher Springer-Verlag
Publication Year 2003
Sub-type Fully published paper
DOI 10.1007/b94701
ISBN 978-3-540-20646-0
ISSN 1611-3349
0302-9743
Editor T. Gideon
L. Fung
Volume 2903
Start page 1003
End page 1013
Total pages 11
Collection year 2003
Language eng
Abstract/Summary 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 (α) 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.
Subjects E1
280207 Pattern Recognition
700199 Computer software and services not elsewhere classified
Keyword Signature verification
Forgery detection
Fuzzy modeling
Box-method
Q-Index Code E1

 
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Created: Fri, 24 Aug 2007, 02:21:48 EST