Beta
ManageSearchChatDiscover
62510

A NEURAL NETWORK APPROACH FOR BLOCK CODING IMAGE COMPRESSION

Article

Last updated: 04 Jan 2025

OverviewSimilar Items

Subjects

-

Tags

-

Abstract

This paper presents a scheme for image compression using block coding by vector quantization technique. This scheme achieves promising results in compression ratio and image quality. Although the encoding time represents a big problem in such solutions, it is improved using a self-organizing feature map (SOFM) neural network. Feature extraction reduces the dimensionality of the problem and enables the neural network to be trained on an image separate from that for testing. Although the time complexity has been reduced, the image quality is also affected by a slight value, which can be accepted in many situations.

DOI

10.21608/iceeng.1999.62510

Keywords

Block Coding, Vector Quantization, Self-Organizing Feature Map, Moment Invariant, Feature Extraction

Authors

First Name

M.

Last Name

IBRAHIM

MiddleName

SHAARAWY

Affiliation

Associate Professor, Dpt. of Computer & OR, Military Technical College, Cairo, Egypt.

Email

-

City

-

Orcid

-

Volume

2

Article Issue

2nd International Conference on Electrical Engineering ICEENG 1999

Related Issue

9420

Issue Date

1999-11-01

Receive Date

2019-11-28

Publish Date

1999-11-01

Page Start

278

Page End

290

Print ISSN

2636-4433

Online ISSN

2636-4441

Article File

ICEENG_Volume 2_Issue 2nd International Conference on Electrical Engineering ICEENG 1999_Pages 278-290.pdf

PDF . 2.6MB

Link

https://iceeng.journals.ekb.eg/article_62510.html

Detail API

https://iceeng.journals.ekb.eg/service?article_code=62510

Order

30

Type

Original Article

Type Code

833

Publication Type

Journal

Publication Title

The International Conference on Electrical Engineering

Publication Link

https://iceeng.journals.ekb.eg/

MainTitle

A NEURAL NETWORK APPROACH FOR BLOCK CODING IMAGE COMPRESSION

Details

Type

Article

Created At

22 Jan 2023