An Investigation of the Effects of Variable Vigilance within the RePART Neuro-Fuzzy Network
Journal of Intelligent and Robotic Systems
A New Fuzzy Character Segmentation Algorithm for Persian / Arabic Typed Texts
Proceedings of the 6th International Conference on Computational Intelligence, Theory and Applications: Fuzzy Days
RePART: A Modified Fuzzy ARTMAP for Pattern Recognition
Proceedings of the 6th International Conference on Computational Intelligence, Theory and Applications: Fuzzy Days
On-line handwritten digit recognition based on trajectory and velocity modeling
Pattern Recognition Letters
New features using fractal multi-dimensions for generalized Arabic font recognition
Pattern Recognition Letters
An Iterative Method for Deciding SVM and Single Layer Neural Network Structures
Neural Processing Letters
Online handwriting recognition for the Arabic letter set
CIT'11 Proceedings of the 5th WSEAS international conference on Communications and information technology
Evaluation Approach of Arabic Character Recognition
International Journal of Computer Vision and Image Processing
An Interactive Device for Quick Arabic News Story Browsing
International Journal of Mobile Computing and Multimedia Communications
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In this paper we describe a system that recognizes on-line Arabic cursive handwriting. In this system, a genetic algorithm is used to select the best combination of characters recognized by a fuzzy neural network. The handwritten words used in this system are modelled by a theory of movement generation. Based on this motor theory, the features extracted from each character are the neuro-physiological and biomechanical parameters of the equation describing the curvilinear velocity of the script. The evolutionary approach proposed here permits the recognition of cursive handwriting with a segmentation procedure allowing overlapped strokes having neuro-physiological meaning.