Co-occurrence Matrix of Oriented Gradients for Word Script and Nature Identification
Identifieur interne : 000386 ( Main/Exploration ); précédent : 000385; suivant : 000387Co-occurrence Matrix of Oriented Gradients for Word Script and Nature Identification
Auteurs : Asma Saïdani [Tunisie] ; Afef Kacem [Tunisie] ; Belaïd Abdel [France]Source :
Abstract
In this paper, we propose a new scheme for scriptand nature identification. The objective is to discriminate betweenmachine-printed/handwritten and Latin/Arabic scripts at wordlevel. It is relatively a complex task due to possible use of multi-fonts and sizes, complexity and variation in handwriting. In theproposed script identification system, we extract features fromword images using Co-occurrence Matrix of Oriented Gradients(Co-MOG). The classification is done using k Nearest Neighbors(k-NN) classifier. Extensive experimentation has been carried on24000 words extracted from standard databases. An averageidentification accuracy of 99.85% is achieved which clearlyoutperforms results of some existing systems
Url:
DOI: 10.5565/rev/elcvia.572
Affiliations:
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<front><div type="abstract" xml:lang="en">In this paper, we propose a new scheme for scriptand nature identification. The objective is to discriminate betweenmachine-printed/handwritten and Latin/Arabic scripts at wordlevel. It is relatively a complex task due to possible use of multi-fonts and sizes, complexity and variation in handwriting. In theproposed script identification system, we extract features fromword images using Co-occurrence Matrix of Oriented Gradients(Co-MOG). The classification is done using k Nearest Neighbors(k-NN) classifier. Extensive experimentation has been carried on24000 words extracted from standard databases. An averageidentification accuracy of 99.85% is achieved which clearlyoutperforms results of some existing systems</div>
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