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dc.contributor.authorAida Nurfarhana, Saidin
dc.date.accessioned2016-05-30T05:17:34Z
dc.date.available2016-05-30T05:17:34Z
dc.date.issued2015-06
dc.identifier.urihttp://dspace.unimap.edu.my:80/xmlui/handle/123456789/41747
dc.descriptionAccess is limited to UniMAP community.en_US
dc.description.abstractSignature is an important biometric of a person that is attribute of a human being which can be used to authenticate human identity. There are lots of biometric techniques that had been represented in the past. A biometric‟s signature verification type had play a very important role in financial, legal transaction and commercial, truly method of authenticating becomes more and more crucial. There are various approaches to signature recognition with a lot of scope of researches. In this project, off- line signature recognition and verification using support vector machine (SVM) is proposed. First, feature vectors are extracted for a reference set of signatures using radon transform. Then, the SVM is trained using a set of genuine and a set of forgery signature. Once trained, the SVM is expected to recognize using an input signature.en_US
dc.language.isoenen_US
dc.publisherUniversiti Malaysia Perlis (UniMAP)en_US
dc.subjectSignatureen_US
dc.subjectBiometric techniquesen_US
dc.subjectSignature recognition systemen_US
dc.subjectSignature verificationen_US
dc.subjectSupport vector machine (SVM)en_US
dc.titleSignature verification and recognition by using support vector machineen_US
dc.typeLearning Objecten_US
dc.contributor.advisorDr. Md Mijanur Rahmanen_US
dc.publisher.departmentSchool of Computer and Communication Engineeringen_US


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