Online signature verification discriminators

Contemporarily, the internet has been heavily used for the electronic commerce especially in the areas of finance and banking. The transactions of the finance and banking on the internet involve use of handwritten signature as a symbol for consent and authorization. Online signature verification is...

Full description

Bibliographic Details
Main Authors: Omar, Nazaruddin, Idris, Norbik Bashah
Format: Conference or Workshop Item
Language:English
Published: 2006
Subjects:
Online Access:http://eprints.utm.my/7786/1/NorbikBashahIdris2006_OnlineSignatureVerificationDiscriminators.pdf
_version_ 1825910098208227328
author Omar, Nazaruddin
Idris, Norbik Bashah
author_facet Omar, Nazaruddin
Idris, Norbik Bashah
author_sort Omar, Nazaruddin
collection ePrints
description Contemporarily, the internet has been heavily used for the electronic commerce especially in the areas of finance and banking. The transactions of the finance and banking on the internet involve use of handwritten signature as a symbol for consent and authorization. Online signature verification is one of the biometric techniques that are widely accepted as personal attribute for identity verification. Hence, it is vital to have an automatic handwritten signature verification system that is fast, reliable and accurate to avoid attempts to forge handwritten signatures, which has resulted in heavy losses for various financial institutions. This paper presents the implementation of an online signature verification system (OSV) using dynamic features as the discriminatos. It will describe the functions and modules of the system, explain on the approach used, and discuss the performance results of the system, which are measured based on the false rejection rate (FRR), and false acceptance rate (FAR). The former means the rate of genuine signatures that are being incorrectly rejected while the latter means that forgeries that are incorrectly accepted. The experimental results showed that the features based on number of stroke, and vertical speed are sufficient to be used to discriminate genuine samples from forgery sample based on the given threshold.
first_indexed 2024-03-05T18:11:58Z
format Conference or Workshop Item
id utm.eprints-7786
institution Universiti Teknologi Malaysia - ePrints
language English
last_indexed 2024-03-05T18:11:58Z
publishDate 2006
record_format dspace
spelling utm.eprints-77862017-08-30T03:56:39Z http://eprints.utm.my/7786/ Online signature verification discriminators Omar, Nazaruddin Idris, Norbik Bashah QA76 Computer software Contemporarily, the internet has been heavily used for the electronic commerce especially in the areas of finance and banking. The transactions of the finance and banking on the internet involve use of handwritten signature as a symbol for consent and authorization. Online signature verification is one of the biometric techniques that are widely accepted as personal attribute for identity verification. Hence, it is vital to have an automatic handwritten signature verification system that is fast, reliable and accurate to avoid attempts to forge handwritten signatures, which has resulted in heavy losses for various financial institutions. This paper presents the implementation of an online signature verification system (OSV) using dynamic features as the discriminatos. It will describe the functions and modules of the system, explain on the approach used, and discuss the performance results of the system, which are measured based on the false rejection rate (FRR), and false acceptance rate (FAR). The former means the rate of genuine signatures that are being incorrectly rejected while the latter means that forgeries that are incorrectly accepted. The experimental results showed that the features based on number of stroke, and vertical speed are sufficient to be used to discriminate genuine samples from forgery sample based on the given threshold. 2006 Conference or Workshop Item NonPeerReviewed application/pdf en http://eprints.utm.my/7786/1/NorbikBashahIdris2006_OnlineSignatureVerificationDiscriminators.pdf Omar, Nazaruddin and Idris, Norbik Bashah (2006) Online signature verification discriminators. In: Proceedings of the Postgraduate Annual Research Seminar 2006 (PARS 2006), 24-25 May 2006, Postgraduate Studies Department FSKSM, UTM Skudai. (Unpublished)
spellingShingle QA76 Computer software
Omar, Nazaruddin
Idris, Norbik Bashah
Online signature verification discriminators
title Online signature verification discriminators
title_full Online signature verification discriminators
title_fullStr Online signature verification discriminators
title_full_unstemmed Online signature verification discriminators
title_short Online signature verification discriminators
title_sort online signature verification discriminators
topic QA76 Computer software
url http://eprints.utm.my/7786/1/NorbikBashahIdris2006_OnlineSignatureVerificationDiscriminators.pdf
work_keys_str_mv AT omarnazaruddin onlinesignatureverificationdiscriminators
AT idrisnorbikbashah onlinesignatureverificationdiscriminators