A new Approach for Online Arabic Handwriting Recognition
نویسندگان
چکیده
One of the most promising methods of interacting with small portable computing devices, such as personal digital assistants, is the use of handwriting. In order to make this communication method more natural, we proposed to visually observe the writing process on ordinary paper and to automatically recover the pen trajectory from numerical tablet sequences. On the basis of this work we developed handwriting recognition system based on Freeman codes similarity. The modelling system is based on beta-elliptical representation. Our experimentations have been released using ADAB dataset. In this paper we will present the different steps of the handwriting recognition system. The results obtained are promising.
منابع مشابه
Off-line Arabic Handwritten Recognition Using a Novel Hybrid HMM-DNN Model
In order to facilitate the entry of data into the computer and its digitalization, automatic recognition of printed texts and manuscripts is one of the considerable aid to many applications. Research on automatic document recognition started decades ago with the recognition of isolated digits and letters, and today, due to advancements in machine learning methods, efforts are being made to iden...
متن کاملAn Approach Based on Structural Segmentation for the Recognition of Arabic Handwriting
Abstract In this paper we propose a new segmentation approach applied to Arabic handwriting, which can reconstruct in offline a tracing path similar to that in the case of online. Our approach uses a semiskeletonization technique for following lines and calculation of the characteristics of characters. With the application of an SVM classifier in the classification phase, we were able to achiev...
متن کاملArabic Online Handwriting Recognition Using Neural Network
This article presents the development of an Arabic online handwriting recognition system. To develop our system, we have chosen the neural network approach. It offers solutions for most of the difficulties linked to Arabic script recognition. We test the approach with our collected databases. This system shows a good result and it has a high accuracy (98.50% for characters, 96.90% for words).
متن کاملOnline Arabic Handwriting Recognition Based on Classifier Combination
Handwriting recognition is a rich and complex issue. Some of its problems include the large shape variations in human handwriting. Classifier combination contributes in increasing the classification accuracy compared to the performance of individual classifier. In this paper, we present an online handwriting recognizer based on classifier combination according to holistic approach. We propose t...
متن کاملMicrosoft Word - CONTENTS-AUGUST07
The last two decades witnessed some advances in the development of an Arabic character recognition (CR) system. Arabic CR faces technical problems not encountered in any other language that make Arabic CR systems achieve relatively low accuracy and retards establishing them as market products. We propose the basic stages towards a system that attacks the problem of recognizing online Arabic cur...
متن کاملA Time Delay Neural Network for Online Arabic Handwriting Recognition
Handwriting recognition is an interesting part in pattern recognition field. In the last decade, several approaches are focused on online handwriting recognition because the very rapid growth of new technologies in the field of data entry. In this paper, we propose a new system for online Arabic handwriting recognition based on beta-elliptic model which allow to segment the trajectory into segm...
متن کامل