A Recognition-Based Approach to Segmenting Arabic Handwritten Text
Open Access
- 1 January 2015
- journal article
- research article
- Published by Scientific Research Publishing, Inc. in Journal of Intelligent Learning Systems and Applications
- Vol. 07 (04), 93-103
- https://doi.org/10.4236/jilsa.2015.74009
Abstract
Segmenting Arabic handwritings had been one of the subjects of research in the field of Arabic character recognition for more than 25 years. The majority of reported segmentation techniques share a critical shortcoming, which is over-segmentation. The aim of segmentation is to produce the letters (segments) of a handwritten word. When a resulting letter (segment) is made of more than one piece (stroke) instead of one, this is called over-segmentation. Our objective is to overcome this problem by using an Artificial Neural Networks (ANN) to verify the resulting segment. We propose a set of heuristic-based rules to assemble strokes in order to report the precise segmented letters. Preprocessing phases that include normalization and feature extraction are required as a prerequisite step for the ANN system for recognition and verification. In our previous work [1], we did achieve a segmentation success rate of 86% but without recognition. In this work, our experimental results confirmed a segmentation success rate of no less than 95%.Keywords
This publication has 14 references indexed in Scilit:
- A Multi-Agent Approach to Arabic Handwritten Text SegmentationJournal of Intelligent Learning Systems and Applications, 2012
- Filtering segmentation cuts for digit string recognitionPattern Recognition, 2008
- Segmentation of connected handwritten numeral stringsPattern Recognition, 2003
- Off-Line Arabic Character Recognition – A ReviewPattern Analysis and Applications, 2002
- Handwritten Farsi (Arabic) word recognition: a holistic approach using discrete HMMPattern Recognition, 2001
- Recognition of printed arabic text based on global features and decision tree learning techniquesPattern Recognition, 2000
- A segmentation-free approach to text recognition with application to Arabic textInternational Journal on Document Analysis and Recognition (IJDAR), 1998
- Off-line Arabic character recognition: the state of the artPattern Recognition, 1998
- Survey and bibliography of Arabic optical text recognitionSignal Processing, 1995
- Automatic recognition of printed Farsi textsPattern Recognition, 1981