Muda, Azah Kamilah and Shamsuddin, Siti Mariyam and Darus, Maslina (2009) Mining generalized features for writer identification. In: 2009 2nd Conference on Data Mining and Optimization, DMO 2009. Institute of Electrical and Electronics Engineers, New York, pp. 32-36. ISBN 978-142444944-6
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Official URL: http://dx.doi.org/10.1109/DMO.2009.5341915
This paper proposes generalized features of various handwriting in forensic documents for writer identification. In forensic documents, graphologies need to scrutinize, analyze and evaluate the features of suspected authors from questioned handwriting and compared these documents with the original handwriting. This is due to the uniqueness of the shape and style of handwriting that can be used for author's authentication. In this study, by acquiring the individuality features from these question documents will lead to the proposed concept of Authorship Invarianceness. However, this paper will focus on Discretization concept that will probe authors' individuality representation by mining the features granularly. This is done by partitioning the attributes into writers' intervals. Our experiments have illustrated that the proposed discretization gives better identification rates compared to non-discretized features.
|Item Type:||Book Section|
|Additional Information:||ISBN: 978-142444944-6; 2009 2nd Conference on Data Mining and Optimization, DMO 2009; Bangi, Selangor; 27 October 2009 through 28 October 2009|
|Uncontrolled Keywords:||authorship invarianceness, forensic document analysis, moment function, writer identification|
|Subjects:||Q Science > QA Mathematics > QA75 Electronic computers. Computer science|
|Divisions:||Computer Science and Information System|
|Deposited By:||Liza Porijo|
|Deposited On:||07 Jul 2011 07:45|
|Last Modified:||07 Jul 2011 07:45|
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