JACIII Vol.13 No.5 pp. 512-519
doi: 10.20965/jaciii.2009.p0512


A Granular Framework for Recognition of Arabic Handwriting

Mokhtar Beldjehem

Sainte Anne University, 1589 Walnut Street Halifax, Nova Scotia, B3H 3S1, Canada

September 19, 2008
February 21 2009
September 20, 2009
granular Arab handwriting recognition, fuzzy and soft computing, morphological analysis, cooperative morphological-guided recognition, approximate fault tolerant recognizer

We propose a novel cognitively motivated unifying framework for Arabic handwriting recognition that takes into account the nature of the human reading process of Arabic handwriting. This Modular Granular Architecture tackles the problem by observing Arabic handwriting from both perceptual and linguistic points of view and hence analyzes the underlying input signal from different granularity levels. It is based on three levels of abstraction: a low granularity level that uses perceptual features called global visual indices, a medium granularity level that is the conventional recognition stage and a high granularity level that consists on morphological analysis dedicated to segmentation/recognition. The original idea is the effective use of Arabic word’s morphology in the recognition not only in post-processing. This architecture carries well around the Arabic word’s morphology, as typically in Arabic, the Arabic word’s morphology is by excellence the logical structure (even semantic) of a given Arabic word, whereas the visual data constitute the physical geometric (topological) structure of a given word. We need to integrate both of them for an effective cooperative recognition of Arabic Handwriting. This framework subsumes the lexicon-driven approaches; in that it can recognize a word that does not exist within the lexicon.

Cite this article as:
M. Beldjehem, “A Granular Framework for Recognition of Arabic Handwriting,” J. Adv. Comput. Intell. Intell. Inform., Vol.13, No.5, pp. 512-519, 2009.
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