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142390

Hand Printed Characters Recognition Using Wavelet Features and Neural Networks.

Article

Last updated: 22 Jan 2023

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Subjects

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Tags

Electrical Engineering

Abstract

Simplifying automatic recognition algorithms for hand-printed characters attracted immense research efforts [1-3]. Character recognition systems can improve the interaction between man and machine in many applications, including office automation, business and data entry applications. This paper introduces the use of bi-dimensional wavelet as features extractor that is feed to Artificial Neural Networks (ANNs) for recognition Latin hand-printed characters. An experiment to verify the efficiency of the system was performed. The proposed technique can be divided into three major steps: the first step is pre-processing in which the original image is transformed into a digitized image utilizing a 300 dpi scanner. Second, feature extraction using wavelets Finally, multilayer artificial neural network is used for characters recognition. 

DOI

10.21608/bfemu.2021.142390

Keywords

Pattern Recognition, wavelet, Feature Extraction, Neural network

Authors

First Name

I.

Last Name

El-Nahry

MiddleName

F.

Affiliation

Department., of Electrical Engineering., Suez Canal University., Port-Said, Egypt.

Email

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City

Suez

Orcid

-

Volume

28

Article Issue

4

Related Issue

20838

Issue Date

2003-12-01

Receive Date

2003-10-11

Publish Date

2021-01-23

Page Start

11

Page End

20

Print ISSN

1110-0923

Online ISSN

2735-4202

Article File

BFEMU_Volume 28_Issue 4_Pages 11-20.pdf

PDF . 180.0kB

Link

https://bfemu.journals.ekb.eg/article_142390.html

Detail API

https://bfemu.journals.ekb.eg/service?article_code=142390

Order

4

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