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dc.contributor.author Muhammad Saifullah Khan, Bilal Ahmad Muhammad Mahad Tariq
dc.date.accessioned 2021-01-13T09:19:41Z
dc.date.available 2021-01-13T09:19:41Z
dc.date.issued 2018
dc.identifier.uri http://10.250.8.41:8080/xmlui/handle/123456789/21078
dc.description Supervisor: Dr. Muhammad Imran Malik en_US
dc.description.abstract Signature verification is the process of using machine learning methods to validate the authenticity of an individual's signature. Signatures can be of one of the two types; on-line or off-line, and this project focuses on off-line signature verification. Aim of this project is to design an algorithm which can distinguish between genuine and forged signatures using writer independent features, and to develop a system using this algorithm which can be used to verify signatures on bank cheques. We intend to build a complete end-to-end hardware/software system which can be used to acquire signatures from bank cheques, perform signature verification, and display the results. For this purpose, various deep learning techniques were developed and tested on standard datasets for off-line signature verification, as well as on a dataset collected by ourselves. en_US
dc.publisher SEECS, National University of Sciences and Technology, Islamabad en_US
dc.subject Software Engineering en_US
dc.title Signature Verification en_US
dc.type Thesis en_US


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