Mustafa Ali Abuzaraida, Akram M Zeki, Ahmed M Zeki
Abstract
Online recognition of Arabic handwritten text has
been an on-going research problem for many years. Generally,
online text recognition field has been gaining more interest
lately due to the increasing popularity of hand-held computers,
digital notebooks and advanced cellular phones. However,
different techniques have been used to build several online
handwritten recognition systems for Arabic text, such as
Neural Networks, Hidden Markov Model, Template Matching
and others. Most of the researches on online text recognition
have divided the recognition system into these three main
phases which are preprocessing phase, feature extraction phase
and recognition phase which considers as the most important
phase and the heart of the whole system. This paper presents
and compares techniques that have been used to recognize the
Arabic handwriting scripts in online recognition systems.
Those techniques attempt to recognize Arabic handwritten
words, characters, digits or strokes. The structure and
strategy of those reviewed techniques are explained in this
article. The strengths and weaknesses of using these techniques
will also be discussed.
Publication Date
11/26/2012
Publisher
IEEE
Keywords
Text Recognition, Recognition Engine, Online
Arabic recognition system
مصطفى علي ابوزريدة | Mustafa Ali Abuzaraida | 12375