A Toolkit for Teaching Arabic Handwriting

CITlab ARGUS for Arabic Handwriting

In recent years, it has been shown that multidimensional recurrent neural networks (MDRNN) perform very well in offline handwriting recognition problems like the OpenHaRT 2013 Document Image Recognition (DIR) task. With suitable writing preprocessing and dictionary lookup, our ARGUS software completed this task with an error rate of 26.27% in its primary setup. Keywords—handwriting recognition,...

A Tool for Arabic Handwriting Training

The percentage of people who produce a neat and clear handwriting is declining sharply. The traditional approach for handwriting teaching is to have a dedicated teacher for long hours of handwriting practice. Unfortunately, this is not feasible in many cases. In this paper we introduce an automated tool for teaching Arabic handwriting using tablet PCs and on-line handwriting recognition techniq...

Arabic Handwriting Recognition

This thesis explores a number of different techniques for use in the field of Arabic Handwriting Recognition. A review of previous work in the field is conducted, and then various techniques are explored in the context of classifying town names from the IFN/ENIT database. A baseline-finding algorithm using Principal Components Analysis is implemented, and the change in performance from reducing...

Skeletonization Algorithm for an Arabic Handwriting

In this paper, we propose a thinning algorithm for Arabic handwriting using color coding for both thinning processing and gap recovery in the final output skeleton. This algorithm is designed so that it accepts unconstrained Arabic handwriting. Different colors have been given to different pixels of interest on the original image in the beginning and during the process of skeletonization. Color...

Multi-agent Systems for Arabic Handwriting Recognition