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.

• Type: Conference
• Year: 2009
• Where: ICDAR
• Authors: Abdelkarim Elbaati, Houcine Boubaker, Monji Kherallah, Abdel Ennaji, Haikal El Abed, Adel M. Alimi
• Keywords: Document Analysis, ICDAR 2009, Off-line Handwriting Recognition, Off-line Trajectory, Temporal Order Restoration