An Automatic Off-Line Signature Verification and Forgery Detection System

An Automatic Off-Line Signature Verification and Forgery Detection System

Vamsi Krishna Madasu (Queensland University of Technology, Australia) and Brian C. Lovell (NICTA Limited (Queensland Laboratory) and University of Queensland, Australia)
Copyright: © 2008 |Pages: 27
DOI: 10.4018/978-1-59904-807-9.ch004
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Abstract

This chapter presents an off-line signature verification and forgery detection system based on fuzzy modeling. The various handwritten signature characteristics and features are first studied and encapsulated to devise a robust verification system. The verification of genuine signatures and detection of forgeries is achieved via angle features extracted using a grid method. The derived features are fuzzified by an exponential membership function, which is modified to include two structural parameters. The structural parameters are devised to take account of possible variations due to handwriting styles and to reflect other factors affecting the scripting of a signature. The efficacy of the proposed system is tested on a large database of signatures comprising more than 1,200 signature images obtained from 40 volunteers.

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