An Automatic Off-Line Signature Verification and Forgery Detection System

Author:

Madasu Vamsi Krishna1,Lovell Brian C.2

Affiliation:

1. Queensland University of Technology, Australia

2. NICTA Limited (Queensland Laboratory) and University of Queensland, Australia

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.

Publisher

IGI Global

Cited by 6 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Introduction to Presentation Attacks in Signature Biometrics and Recent Advances;Handbook of Biometric Anti-Spoofing;2023

2. Presentation Attacks in Signature Biometrics: Types and Introduction to Attack Detection;Handbook of Biometric Anti-Spoofing;2019

3. Hybrid Rough Neural Network Model for Signature Recognition;Advances in Soft Computing and Machine Learning in Image Processing;2017-10-15

4. Online signature verification by spectrogram analysis;Applied Intelligence;2017-08-01

5. Hidden Frequency Feature in Electronic Signatures;Trends in Applied Knowledge-Based Systems and Data Science;2016

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