This work presents a single feature extraction algorithm that is being used successfully in text recognition for Arabic, English and Bangla. Each of these languages represents a language family. Arabic might represent Arabic, Urdu, Farsi and other right to left languages. English might represent Latin languages including French and Spanish as examples. Bangla might be a representative of Indic languages such as Hindi. The novelty of this work lies in the fact that it depends on a single type of features, which is the density distribution of the text images. This simple feature extraction method is tested on different languages to investigate its efficiency.
3rd Mosharaka International Conference on Communications, Computers and Applications (MIC-CCA 2009)
Congress
2009 Global Congress on Communications, Computers and Applications (GC-CCA 2009), 26-28 October 2009, Amman, Jordan
Pages
--1
Topics
ISSN
2227-331X
DOI
BibTeX
@inproceedings{758CCA2009,
title={A single feature extraction algorithm for text recognition of different families of languages},
author={Husni A. Al-Muhtaseb, and Rami S. Qahwaji},
booktitle={2009 Global Congress on Communications, Computers and Applications (GC-CCA 2009)},
year={2009},
pages={--1},
doi={}},
organization={Mosharaka for Research and Studies}
}
