Unconstrained Arabic Handwritten Word Feature Extraction: A Comparative Study

J. H. AlKhateeb; Jinchang Ren; J. Jiang; S. Ipson

doi:10.1109/ITNG.2009.222

Unconstrained Arabic Handwritten Word Feature Extraction: A Comparative Study

J. H. AlKhateeb, Jinchang Ren, J. Jiang , S. Ipson

Electronic And Electrical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution book

1 Citation (Scopus)

Abstract

This paper presents an overview of feature extraction techniques for unconstrained Arabic handwritten word recognition. Choosing a technique for extraction the features considers the most important factor in achieving high recognition rates in word or character recognition. Different techniques were designed to extract the features from the Arabic words. These techniques are presented and discussed in terms of invariant invariance properties.

Original language	English
Title of host publication	Proceedings of the 2009 Sixth International Conference on Information Technology: New Generations
Subtitle of host publication	ITNG 2009
Publisher	IEEE
Pages	1655-1656
Number of pages	2
ISBN (Print)	978-1-4244-3770-2
DOIs	https://doi.org/10.1109/ITNG.2009.222
Publication status	Published - 2009
Event	Sixth International Conference on Information Technology - Las Vegas, United States Duration: 27 Apr 2009 → 29 Apr 2009

Conference

Conference	Sixth International Conference on Information Technology
Country	United States
City	Las Vegas
Period	27/04/09 → 29/04/09

Keywords

application software
character recognition
discrete cosine transforms
feature extraction
testing
skeleton
hidden Markov models
optical character recognition software
image segmentation

Access to Document

10.1109/ITNG.2009.222

http://dx.doi.org/10.1109/ITNG.2009.222

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Cite this

@inproceedings{8bbbe72afb324922a16c96af08f74b7c,

title = "Unconstrained Arabic Handwritten Word Feature Extraction: A Comparative Study",

abstract = "This paper presents an overview of feature extraction techniques for unconstrained Arabic handwritten word recognition. Choosing a technique for extraction the features considers the most important factor in achieving high recognition rates in word or character recognition. Different techniques were designed to extract the features from the Arabic words. These techniques are presented and discussed in terms of invariant invariance properties.",

keywords = "application software, character recognition, discrete cosine transforms , feature extraction , testing, skeleton, hidden Markov models, optical character recognition software, image segmentation ",

author = "AlKhateeb, {J. H.} and Jinchang Ren and J. Jiang and S. Ipson",

year = "2009",

doi = "10.1109/ITNG.2009.222",

language = "English",

isbn = "978-1-4244-3770-2",

pages = "1655--1656",

booktitle = "Proceedings of the 2009 Sixth International Conference on Information Technology: New Generations",

publisher = "IEEE",

note = "Sixth International Conference on Information Technology ; Conference date: 27-04-2009 Through 29-04-2009",

}

AlKhateeb, JH, Ren, J, Jiang , J & Ipson, S 2009, Unconstrained Arabic Handwritten Word Feature Extraction: A Comparative Study. in Proceedings of the 2009 Sixth International Conference on Information Technology: New Generations: ITNG 2009. IEEE, pp. 1655-1656, Sixth International Conference on Information Technology, Las Vegas, United States, 27/04/09. https://doi.org/10.1109/ITNG.2009.222

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AU - Ren, Jinchang

AU - Jiang , J.

AU - Ipson, S.

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AB - This paper presents an overview of feature extraction techniques for unconstrained Arabic handwritten word recognition. Choosing a technique for extraction the features considers the most important factor in achieving high recognition rates in word or character recognition. Different techniques were designed to extract the features from the Arabic words. These techniques are presented and discussed in terms of invariant invariance properties.

KW - application software

KW - character recognition

KW - discrete cosine transforms

KW - feature extraction

KW - testing

KW - skeleton

KW - hidden Markov models

KW - optical character recognition software

KW - image segmentation

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M3 - Conference contribution book

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BT - Proceedings of the 2009 Sixth International Conference on Information Technology: New Generations

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