Publication: A hybrid statistical modelling, normalization and inferencing techniques of an off-line signature verification system
Date
2009
Authors
Ahmad S.M.S.
Shakil A.
Faudzi M.A.
Anwar R.Md.
Balbed M.A.M.
Journal Title
Journal ISSN
Volume Title
Publisher
Abstract
This paper presents an automatic off-line signature verification system that is built using several statistical techniques .The learning phase involves the use of Hidden Markov Modelling (HMM) technique to build a reference model for each local feature extracted from a set of signature samples of a particular user. The verification phase uses three layers of statistical techniques.. The first layer involves the computation of the HMM-based log-likelihood probability match score. The second layer performs the mapping of this score into soft boundary ranges of acceptance or rejection through the use of z-score analysis and normalization function. Next Bayesian inference technique is used to arrive at the final decision of accepting or rejecting a given signature sample. � 2008 IEEE.
Description
Keywords
Bayesian inference , Hidden Markov Model (HMM) , Computer science , Hidden Markov models , Inference engines , Probability density function , Bayesian inference , Final decision , Hidden Markov Model (HMM) , Learning phase , Local feature , Log likelihood , Match score , Off-line signature verification , Reference models , Second layer , Statistical modelling , Statistical techniques , Three-layer , Z-score analysis , Bayesian networks