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132761

Arabic Document Image Classification Using Neural Networks.

Article

Last updated: 22 Jan 2023

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Subjects

-

Tags

Electrical Engineering

Abstract

The Neural Network Arabic Document Image Classification System (NNADICS) is an adaptive Arabic document classifier. By training NNADICS on a number of different document image types, NNADICS behaves as a multiple classifier, since it is capable for distinguishing between multiple document image types. NNADICS is designed, built, tested and evaluated. After training NNADICS a document image is applied to the system for classification. Before that the document image is scanned, pre-processed and binarized, and then applied to NNADICS to classify its contents to text, geometric, or photographic image type. NNADICS achieved an average of a 86% recognition rate as it is clearly demonstrated.

DOI

10.21608/bfemu.2020.132761

Authors

First Name

Abdallah

Last Name

Al-Khorabi

MiddleName

-

Affiliation

Sana'a University, Sana'a, Yemen Republic P. 0. Box 1341, Fax 967-1-2505 14

Email

alkhorabi@vahoo.com

City

-

Orcid

-

First Name

Mohamed

Last Name

Mansour

MiddleName

Abduallah

Affiliation

Postgraduate Student University of Science and Technology Sana'a, Yemen Republic P, 0, Box 1341

Email

mhsaadanym@mans.edu.eg

City

-

Orcid

0000-0003-3575-0373

Volume

29

Article Issue

1

Related Issue

19655

Issue Date

2004-03-01

Receive Date

2003-12-11

Publish Date

2020-12-27

Page Start

56

Page End

63

Print ISSN

1110-0923

Online ISSN

2735-4202

Article File

BFEMU_Volume 29_Issue 1_Pages 56-63.pdf

PDF . 223.4kB

Link

https://bfemu.journals.ekb.eg/article_132761.html

Detail API

https://bfemu.journals.ekb.eg/service?article_code=132761

Order

18

Type

Research Studies

Type Code

1,205

Publication Type

Journal

Publication Title

MEJ. Mansoura Engineering Journal

Publication Link

https://bfemu.journals.ekb.eg/

MainTitle

-

Details

Type

Article

Created At

22 Jan 2023