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Invariant behavioural based discrimination for individual representation

Wong, Yee Leng and Shamsuddin, Siti Mariyam and Hashim, Nor Azman (2021) Invariant behavioural based discrimination for individual representation. International Journal of Electrical and Computer Engineering, 11 (1). pp. 736-744. ISSN 2088-8708

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Official URL: http://dx.doi.org/10.11591/ijece.v11i1.pp736-744

Abstract

Writer identification based on cursive words is one of the extensive behavioural biometric that has involved many researchers to work in. Recently, its main idea is in forensic investigation and biometric analysis as such the handwriting style can be used as individual behavioural adaptation for authenticating an author. In this study, a novel approach of presenting cursive features of authors is presented. The invariants-based discriminability of the features is proposed by discretizing the moment features of each writer using biometric invariant discretization cutting point (BIDCP). BIDCP is introduced for features perseverance to obtain better individual representations and discriminations. Our experiments have revealed that by using the proposed method, the authorship identification based on cursive words is significantly increased with an average identification rate of 99.80%.

Item Type:Article
Uncontrolled Keywords:data mining, discretization, identification
Subjects:Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions:Computing
ID Code:94030
Deposited By: Yanti Mohd Shah
Deposited On:28 Feb 2022 13:31
Last Modified:28 Feb 2022 13:31

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