InforLorV4, Main, Exploration, bibRecord, 000389

A Recognition based Approach for Segmenting Touching Components in Arabic Manuscripts

Identifieur interne : 000389 ( Main/Exploration ); précédent : 000388; suivant : 000390

A Recognition based Approach for Segmenting Touching Components in Arabic Manuscripts

Auteurs : Nabil Aouadi [Tunisie] ; Afef Kacem [Tunisie] ; Belaïd Abdel [France]

Source :

RBID : Hal:hal-01254711

Abstract

This work aims to segment touching components (TCs) which may occur between word letters of consecutive text-lines or those of words of the same line in Arabic manuscripts. The proposed approach is mainly based on two steps: 1) finding for a localized touching component its most similar model, stored in a dictionary with its correct segmentation, based on shape context descriptor, 2) segmenting the touching component based on central point of the found most similar model's parts. Tests are performed using a database of connection zones (1300 samples) and three metrics: Manhattan, Euclidean and Canberra distances. Experimental results have shown the effectiveness of the proposed touching component segmentation method in comparison to some related works. Our best achieved TC segmentation rate is of 94%.

Url:

https://hal.inria.fr/hal-01254711

DOI: 10.1109/ICDAR.2015.7333718

Affiliations:

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to stream Hal, to step Corpus: 000423
to stream Hal, to step Curation: 000423
to stream Hal, to step Checkpoint: 000366
to stream Main, to step Merge: 000389
to stream Main, to step Curation: 000389

Le document en format XML

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<front><div type="abstract" xml:lang="en">This work aims to segment touching components (TCs) which may occur between word letters of consecutive text-lines or those of words of the same line in Arabic manuscripts. The proposed approach is mainly based on two steps: 1) finding for a localized touching component its most similar model, stored in a dictionary with its correct segmentation, based on shape context descriptor, 2) segmenting the touching component based on central point of the found most similar model's parts. Tests are performed using a database of connection zones (1300 samples) and three metrics: Manhattan, Euclidean and Canberra distances. Experimental results have shown the effectiveness of the proposed touching component segmentation method in comparison to some related works. Our best achieved TC segmentation rate is of 94%.</div>
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A Recognition based Approach for Segmenting Touching Components in Arabic Manuscripts

A Recognition based Approach for Segmenting Touching Components in Arabic Manuscripts

Source :

Abstract

Links toward previous steps (curation, corpus...)

Le document en format XML

Pour manipuler ce document sous Unix (Dilib)

Pour mettre un lien sur cette page dans le réseau Wicri