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Semantic Document Layout Analysis of Handwritten Manuscripts

Emad Sami Jaha*

Department of Computer Science, Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah, 21589, Saudi Arabia

* Corresponding Author: Emad Sami Jaha. Email: email

Computers, Materials & Continua 2023, 75(2), 2805-2831. https://doi.org/10.32604/cmc.2023.036169

Abstract

A document layout can be more informative than merely a document’s visual and structural appearance. Thus, document layout analysis (DLA) is considered a necessary prerequisite for advanced processing and detailed document image analysis to be further used in several applications and different objectives. This research extends the traditional approaches of DLA and introduces the concept of semantic document layout analysis (SDLA) by proposing a novel framework for semantic layout analysis and characterization of handwritten manuscripts. The proposed SDLA approach enables the derivation of implicit information and semantic characteristics, which can be effectively utilized in dozens of practical applications for various purposes, in a way bridging the semantic gap and providing more understandable high-level document image analysis and more invariant characterization via absolute and relative labeling. This approach is validated and evaluated on a large dataset of Arabic handwritten manuscripts comprising complex layouts. The experimental work shows promising results in terms of accurate and effective semantic characteristic-based clustering and retrieval of handwritten manuscripts. It also indicates the expected efficacy of using the capabilities of the proposed approach in automating and facilitating many functional, real-life tasks such as effort estimation and pricing of transcription or typing of such complex manuscripts.

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Cite This Article

E. S. Jaha, "Semantic document layout analysis of handwritten manuscripts," Computers, Materials & Continua, vol. 75, no.2, pp. 2805–2831, 2023. https://doi.org/10.32604/cmc.2023.036169



cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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