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

Slim Kanoun (1) , Adel Alimi (1) , Yves Lecourtier (2)

1 REGIM-Lab - REsearch Group in Intelligent Machines [Sfax]
2 LITIS - Laboratoire d'Informatique, de Traitement de l'Information et des Systèmes

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).

Domains: Document and Text Processing

Slim Kanoun, Adel Alimi, Yves Lecourtier. Natural Language Morphology Integration in Off-Line Arabic Optical Text Recognition. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, 2011, 41 (2), pp.579-590. ⟨hal-00591943⟩