Arabic Online Handwriting Recognition: A Survey AbdulMalik Al-Salman Department of Computer Science King Saud University Saudi Arabia Salman@ksu.edu.sa Haifa Alyahya Department of Computer Science King Saud University Saudi Arabia h.yahya@uoh.edu.sa ABSTRACT Nowadays, Arabic handwriting recognition is an active research area. The optical character recognition is classified into two approaches offline and online. There are many studies and applications for Arabic offline recognition, both typed and handwritten, yet there are few studies on Arabic Online recognition. Online recognition, in general, is oriented to only handwritten. The cursive, shapes, dots and delayed strokes of Arabic letters are the most challenging tasks to develop and improve an online system for the Arabic language. Moreover, handwriting of many Arab people becomes poor with low handwriting skills, especially after the cancellation of the Arabic calligraphy subject in the educational system in many Arabic countries. This paper presents a comprehensive survey on Arabic online handwriting recognition for the past few years. The paper aims to elevate the research in this subject, reveal the avenues for improving the recognition of Arabic online handwriting and enhance the skills of the Arab people in handwriting via online teaching and training system. CCS CONCEPTS  Pattern Recognition → Image Processing; Arabic Optical Character Recognition  Survey → Arabic Online Handwriting Recognition KEYWORDS Handwriting recognition, Arabic, OCR, online recognition __________________________ Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from Permissions@acm.org. IML '17, October 17-18, 2017, Liverpool, United Kingdom © 2017 Association for Computing Machinery. ACM ISBN978-1-4503-5243-7/17/10…$15.00 http://dx.doi.org/10.1145/3109761.3158377 1 INTRODUCTION Character recognition system can be categorized into two category: printed character and handwriting characters. In this paper, we focus on handwriting character only. Figure 1 shows the flowchart of the character recognition system. Written language recognition is the task of transforming a language represented in its spatial form of graphical marks into its symbolic representation [1]. Figure 1. Character recognition systems [2]. Handwritten Character Recognition (HCR) is classified into two different approaches: Offline recognition is performed on images of handwritten text. Online handwriting, the location of the pen-tip on a surface is recorded at regular intervals, and the task is to map from the sequence of pen positions to the sequence of words. The main difference between them is that in an on-line system the recognition is performed at the time of writing (e.g. tablet, smart phone) while the off-line handwritten recognition is performed after the writing is completed (e.g. scanned document) [11]. Also, several studies show that the on-line character recognition methods give high recognition rates and high accuracy than the Offline.