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

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

TY - GEN

T1 - Unconstrained Arabic Handwritten Word Feature Extraction: A Comparative Study

AU - AlKhateeb, J. H.

AU - Ren, Jinchang

AU - Jiang , J.

AU - Ipson, S.

PY - 2009

Y1 - 2009

N2 - 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.

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

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

U2 - 10.1109/ITNG.2009.222

DO - 10.1109/ITNG.2009.222

M3 - Conference contribution book

SN - 978-1-4244-3770-2

SP - 1655

EP - 1656

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

PB - IEEE

T2 - Sixth International Conference on Information Technology

Y2 - 27 April 2009 through 29 April 2009

ER -

Unconstrained Arabic Handwritten Word Feature Extraction: A Comparative Study

Abstract

Conference

Keywords

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