Signature verification and forgery detection system


M. H. M. Yusof, and Madasu, V. K. (2003) Signature verification and forgery detection system. In: Proceedings. Student Conference Research and Development, 2003. SCORED 2003. IEEE Xplore, pp. 9-14. ISBN 0-7803-8173-4

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This paper presents an innovative approach for signature verification and forgery detection based on fuzzy modeling. The signature images are binarized and resized to a fixed size window and are 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) and distance (γ) from each box. Each feature extracted from sample signatures gives rise to fuzzy sets. 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
Subjects: T Technology > T Technology (General)
Divisions: Faculty of Information Science and Technology (FIST)
Depositing User: Ms Suzilawati Abu Samah
Date Deposited: 24 Dec 2013 01:44
Last Modified: 24 Dec 2013 01:44


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