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Co-occurrence Matrix of Oriented Gradients for Word Script and Nature Identification

Abstract : In this paper, we propose a new scheme for script and nature identification. The objective is to discriminate between machine-printed/handwritten and Latin/Arabic scripts at word level. It is relatively a complex task due to possible use of multi-fonts and sizes, complexity and variation in handwriting. In the proposed script identification system, we extract features from word 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 on 24000 words extracted from standard databases. An average identification accuracy of 99.85% is achieved which clearly outperforms results of some existing systems
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https://hal.inria.fr/hal-01254691
Contributor : Abdel Belaid <>
Submitted on : Tuesday, January 12, 2016 - 3:40:24 PM
Last modification on : Friday, January 15, 2021 - 5:42:02 PM

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Asma Saïdani, Afef Kacem, Belaïd Abdel. Co-occurrence Matrix of Oriented Gradients for Word Script and Nature Identification. International Conference on Document Analysis and Recognition, Aug 2015, Nancy, France. ⟨10.5565/rev/elcvia.572⟩. ⟨hal-01254691⟩

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