An Improved Arabic On-Line Characters Recognition System

Abstract

This work presents survey, implementation and test for a neural network: TDNN (Time Delay Neural Network), applied to on-line handwritten recognition characters. In this work, we present a recognizer conception for on-line Arabic handwriting. On-line handwriting recognition of Arabic script is a complex problem, since it is naturally both cursive and unconstrained. This system permits to interpret a script represented by the pen trajectory. This technique is used notably in the electronic tablets. We will construct a data base with several scripters. Afterwards, and before attacking the recognition phase, there is a constructional samples phase of Arabic characters acquired from an electronic tablet to digitize (NOUN DATABASE). Obtained scores shows an effectiveness of the proposed approach based on convolutional neural networks.