Neural network based segmentation algorithm for Arabic characters recognition

Abstract EN

This paper presents a novel holistic technique for classifying Arabic handwritten text documents, which it is performed in several steps.

First, the Arabic handwritten document images are segmented into their connected parts.

A simple heuristic segmentation algorithm is used which finds segmentation points in printed and cursive handwritten words.

Second, several features are extracted from these connected parts and then combined to represent a word with one consolidated feature vector.

Finally, Neocognitron type of the neural network is used to learn and classify the different fonts into word classes.