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

4 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
Ahmad, Sharifah Mumtazah Syed ; Shakil, Asma ; Admad Faudzi, Masyura ; Md. Anwar, Rina ; Balbed, Mustafa Agil Muhamad. / A hybrid statistical modelling, normalization and inferencing techniques of an off-line signature verification system. 2009 WRI World Congress on Computer Science and Information Engineering, CSIE 2009. Vol. 6 2009. pp. 6-11
@inproceedings{4c8e5a5d7f2a46ae98e59e5732aca46b,
title = "A hybrid statistical modelling, normalization and inferencing techniques of an off-line signature verification system",
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.",
author = "Ahmad, {Sharifah Mumtazah Syed} and Asma Shakil and {Admad Faudzi}, Masyura and {Md. Anwar}, Rina and Balbed, {Mustafa Agil Muhamad}",
year = "2009",
month = "11",
day = "16",
doi = "10.1109/CSIE.2009.973",
language = "English",
isbn = "9780769535074",
volume = "6",
pages = "6--11",
booktitle = "2009 WRI World Congress on Computer Science and Information Engineering, CSIE 2009",

}

Ahmad, SMS, Shakil, A, Admad Faudzi, M, Md. Anwar, R & Balbed, MAM 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, 5170651, pp. 6-11, 2009 WRI World Congress on Computer Science and Information Engineering, CSIE 2009, Los Angeles, CA, United States, 31/03/09. https://doi.org/10.1109/CSIE.2009.973

A hybrid statistical modelling, normalization and inferencing techniques of an off-line signature verification system. / Ahmad, Sharifah Mumtazah Syed; Shakil, Asma; Admad Faudzi, Masyura; Md. Anwar, Rina; Balbed, Mustafa Agil Muhamad.

2009 WRI World Congress on Computer Science and Information Engineering, CSIE 2009. Vol. 6 2009. p. 6-11 5170651.

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

TY - GEN

T1 - A hybrid statistical modelling, normalization and inferencing techniques of an off-line signature verification system

AU - Ahmad, Sharifah Mumtazah Syed

AU - Shakil, Asma

AU - Admad Faudzi, Masyura

AU - Md. Anwar, Rina

AU - Balbed, Mustafa Agil Muhamad

PY - 2009/11/16

Y1 - 2009/11/16

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=71049169291&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=71049169291&partnerID=8YFLogxK

U2 - 10.1109/CSIE.2009.973

DO - 10.1109/CSIE.2009.973

M3 - Conference contribution

AN - SCOPUS:71049169291

SN - 9780769535074

VL - 6

SP - 6

EP - 11

BT - 2009 WRI World Congress on Computer Science and Information Engineering, CSIE 2009

ER -

Ahmad SMS, Shakil A, Admad Faudzi M, Md. Anwar R, Balbed MAM. 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. 2009. p. 6-11. 5170651 https://doi.org/10.1109/CSIE.2009.973