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Title: | A hybrid statistical modelling, normalization and inferencing techniques of an off-line signature verification system | Authors: | Ahmad, S.M.S. Shakil, A. Faudzi, M.A. Anwar, R.Md. Balbed, M.A.M. |
Issue Date: | 2009 | Journal: | In 2009 WRI World Congress on Computer Science and Information Engineering, CSIE 2009 (Vol. 6, pp. 6-11). [5170651] | 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. | DOI: | 10.1109/CSIE.2009.973 |
Appears in Collections: | CCI Scholarly Publication |
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