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Recognition-Based Segmentation of Nom Characters from Body Text Regions of Stele Images Using Area Voronoi Diagram

Identifieur interne : 000920 ( Main/Exploration ); précédent : 000919; suivant : 000921

Recognition-Based Segmentation of Nom Characters from Body Text Regions of Stele Images Using Area Voronoi Diagram

Auteurs : V. Hoang [Viêt Nam, France] ; Salvatore Tabbone [France] ; Ngoc-Yen Pham [Viêt Nam]

Source :

RBID : ISTEX:10ACEFF10D679878C336ED2CD736C58908395270

Abstract

Abstract: Segmentation of Nom characters from body text regions of stele images is a challenging problem due to the confusing spatial distribution of the connected components composing these characters. In this paper, for each vertical text line, area Voronoi diagram is employed to represent the neighborhood of the connected components and Voronoi edges are used as nonlinear segmentation hypotheses. Characters are then segmented by selecting appropriate adjacent Voronoi regions. For this purpose, we utilize the information about the horizontal overlap of connected components and the recognition distances of candidate characters provided by an OCR engine. Experimental results show that the proposed method is highly accurate and robust to various types of stele.

Url:
DOI: 10.1007/978-3-642-03767-2_25


Affiliations:


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<div type="abstract" xml:lang="en">Abstract: Segmentation of Nom characters from body text regions of stele images is a challenging problem due to the confusing spatial distribution of the connected components composing these characters. In this paper, for each vertical text line, area Voronoi diagram is employed to represent the neighborhood of the connected components and Voronoi edges are used as nonlinear segmentation hypotheses. Characters are then segmented by selecting appropriate adjacent Voronoi regions. For this purpose, we utilize the information about the horizontal overlap of connected components and the recognition distances of candidate characters provided by an OCR engine. Experimental results show that the proposed method is highly accurate and robust to various types of stele.</div>
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