Publication:
Analysis of 'goat' within user population of an offline signature biometrics

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dc.citedby4
dc.contributor.authorSharifah M.S.A.en_US
dc.contributor.authorAsma S.en_US
dc.contributor.authorMasyura A.F.en_US
dc.contributor.authorRina M.A.en_US
dc.contributor.authorid36680916600en_US
dc.contributor.authorid24722081200en_US
dc.contributor.authorid35193815200en_US
dc.contributor.authorid24721188400en_US
dc.date.accessioned2023-12-28T07:17:47Z
dc.date.available2023-12-28T07:17:47Z
dc.date.issued2010
dc.description.abstractIntra - user variability inherent in human handwritten signatures remains one of the main challenges for a robust biometrics signature based authentication system. The existence of a subset of users classified as 'goats' in the Doddington's menagerie whose signature samples are highly inconsistent and often rejected by the biometrics system may degrade the system accuracy by contributing a large portion to the False Rejection Rate (FRR). However, little is known on the level of the intra user variability and percentage of the 'goats' in the overall user population, which in turns remains the prime focus of this paper. An HMM-based computational approach is used to build the reference model and verifY the authenticity of an input sample based on a series of a local feature extracted from signature images. Here, four different goat populations are identified for offline signature biometric system which is based on four different local features ( namely pixel density, centre of gravity, angle, and distance) and are analysed for their co-relationship. The overall analysis is carried out on Sigma database which is compiled to reflect the signatures of a target user population. � 2010 IEEE.en_US
dc.description.natureFinalen_US
dc.identifier.ArtNo5605415
dc.identifier.doi10.1109/ISSPA.2010.5605415
dc.identifier.epage769
dc.identifier.scopus2-s2.0-78650276249
dc.identifier.spage765
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-78650276249&doi=10.1109%2fISSPA.2010.5605415&partnerID=40&md5=24f638ca9ca035f88774e99a8a3f6b08
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/29625
dc.pagecount4
dc.sourceScopus
dc.sourcetitle10th International Conference on Information Sciences, Signal Processing and their Applications, ISSPA 2010
dc.subjectDoddignton's menagerie
dc.subjectHidden markov model (HMM)
dc.subjectZ-Score analysis
dc.subjectHidden Markov models
dc.subjectInformation science
dc.subjectPopulation statistics
dc.subjectSignal processing
dc.subjectAuthentication systems
dc.subjectBiometric systems
dc.subjectCentre of gravity
dc.subjectComputational approach
dc.subjectDoddignton's menagerie
dc.subjectFalse rejection rate
dc.subjectHandwritten signatures
dc.subjectHidden markov model (HMM)
dc.subjectInput sample
dc.subjectLocal feature
dc.subjectOffline signatures
dc.subjectPrime-focus
dc.subjectReference models
dc.subjectSignature images
dc.subjectSystem accuracy
dc.subjectZ-score analysis
dc.subjectBiometrics
dc.titleAnalysis of 'goat' within user population of an offline signature biometricsen_US
dc.typeConference Paperen_US
dspace.entity.typePublication
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