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dc.contributor.author | Dr Shehzad Khalid | |
dc.contributor.author | Israr Uddin Khattak | |
dc.contributor.author | Imran Siddiqi | |
dc.contributor.author | Chawki Djeddi | |
dc.date.accessioned | 2017-11-22T07:08:58Z | |
dc.date.available | 2017-11-22T07:08:58Z | |
dc.date.issued | 2015 | |
dc.identifier.uri | http://hdl.handle.net/123456789/5009 | |
dc.description.abstract | This paper presents an effective segmentation-free and scale-invariant technique for recognition of Urdu ligatures in Nastaliq font. The proposed technique relies on separating the main body of ligatures from the secondary components and training a separate hidden Markov model for each. Features capturing projection, concavity and curvature information of ligatures are extracted using right-to-Ieft sliding windows and are fed to the models for training. The system trained and evaluated on a total of more than 2,000 frequently occurring Urdu ligatures from a standard database realized a recognition rate of 97.93%. | en_US |
dc.language.iso | en | en_US |
dc.publisher | Bahria University Islamabad Campus | en_US |
dc.subject | Department of Computer Engineering CE | en_US |
dc.title | Recognition of Urdu ligatures: A Holistic Approach | en_US |
dc.type | Article | en_US |