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ICDAR
2009
IEEE

Arabic Handwriting Recognition Using Restored Stroke Chronology

10 years 11 months ago
Arabic Handwriting Recognition Using Restored Stroke Chronology
In this paper we present a system of the off-line handwriting recognition. Our recognition system is based on temporal order restoration of the off-line trajectory. For this task we use a genetic algorithm (GA) to optimize the sequences of handwritten strokes. To benefit from dynamic information we make a sampling operation by the consideration of trajectory curvatures. We proceed to calculate the curvilinear velocity signal and use the beta-elliptical modeling which is developed in on-line systems to calculate other characteristics. Our approach is validated by Hidden Markov Model (HMM) Tool Kit (HTK) recognition system using IfN/ENIT database.
Abdelkarim Elbaati, Houcine Boubaker, Monji Kheral
Added 21 May 2010
Updated 21 May 2010
Type Conference
Year 2009
Where ICDAR
Authors Abdelkarim Elbaati, Houcine Boubaker, Monji Kherallah, Abdel Ennaji, Haikal El Abed, Adel M. Alimi
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