A hybrid statistical modelling, normalization and inferencing techniques of an off-line signature verification system

Sharifah Mumtazah Syed Ahmad, Asma Shakil, Masyura Admad Faudzi, Rina Md. Anwar, Mustafa Agil Muhamad Balbed

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Citations (Scopus)

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.

Original languageEnglish
Title of host publication2009 WRI World Congress on Computer Science and Information Engineering, CSIE 2009
Pages6-11
Number of pages6
Volume6
DOIs
Publication statusPublished - 16 Nov 2009
Event2009 WRI World Congress on Computer Science and Information Engineering, CSIE 2009 - Los Angeles, CA, United States
Duration: 31 Mar 200902 Apr 2009

Other

Other2009 WRI World Congress on Computer Science and Information Engineering, CSIE 2009
CountryUnited States
CityLos Angeles, CA
Period31/03/0902/04/09

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Hardware and Architecture
  • Information Systems
  • Software

Cite this

Ahmad, S. M. S., Shakil, A., Admad Faudzi, M., Md. Anwar, R., & Balbed, M. A. M. (2009). A hybrid statistical modelling, normalization and inferencing techniques of an off-line signature verification system. In 2009 WRI World Congress on Computer Science and Information Engineering, CSIE 2009 (Vol. 6, pp. 6-11). [5170651] https://doi.org/10.1109/CSIE.2009.973