OcrV1, Main, Exploration, bibRecord, 000345

Natural Language Morphology Integration in Off-Line Arabic Optical Text Recognition

Identifieur interne : 000345 ( Main/Exploration ); précédent : 000344; suivant : 000346

Natural Language Morphology Integration in Off-Line Arabic Optical Text Recognition

Auteurs : Slim Kanoun [Tunisie] ; Adel Alimi [Tunisie] ; Yves Lecourtier [France]

Source :

IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics [ 1083-4419 ] ; 2011-04.

RBID : Hal:hal-00591943

Abstract

In this paper, we propose a new linguistic-based approach called the affixal approach for Arabic word and text image recognition. Most of the existing works in the field integrate the knowledge of the Arabic language in the recognition process in two ways: either in post-recognition using the language of dictionary (dictionary of words) to validate the word hypotheses suggested by the OCR or in the course of the recognition process (recognition directed by a lexicon) using a statistical model of the language (Hidden Markov Model or N-gram). The proposed approach uses the linguistic concepts of the vocabulary to direct and simplify the recognition process. The principal contribution of the proposed approach is to be able to categorize the word hypotheses in words that are either derived or not derived from roots and to characterize morphologically each word hypothesis in order to prepare the text hypotheses for later analyses (for example, syntactic analysis; to filter the sentence hypotheses).

Url:

https://hal.archives-ouvertes.fr/hal-00591943

Affiliations:

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

to stream Hal, to step Corpus: 000087
to stream Hal, to step Curation: 000087
to stream Hal, to step Checkpoint: 000087
to stream Main, to step Merge: 000350
to stream Main, to step Curation: 000345

Le document en format XML

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<front><div type="abstract" xml:lang="en">In this paper, we propose a new linguistic-based approach called the affixal approach for Arabic word and text image recognition. Most of the existing works in the field integrate the knowledge of the Arabic language in the recognition process in two ways: either in post-recognition using the language of dictionary (dictionary of words) to validate the word hypotheses suggested by the OCR or in the course of the recognition process (recognition directed by a lexicon) using a statistical model of the language (Hidden Markov Model or N-gram). The proposed approach uses the linguistic concepts of the vocabulary to direct and simplify the recognition process. The principal contribution of the proposed approach is to be able to categorize the word hypotheses in words that are either derived or not derived from roots and to characterize morphologically each word hypothesis in order to prepare the text hypotheses for later analyses (for example, syntactic analysis; to filter the sentence hypotheses).</div>
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Natural Language Morphology Integration in Off-Line Arabic Optical Text Recognition

Natural Language Morphology Integration in Off-Line Arabic Optical Text Recognition

Source :

Abstract

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

Le document en format XML

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