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278978

Image Segmentation Using Hybrid Optimization Algorithms: Review

Article

Last updated: 23 Jan 2023

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Abstract

Image segmentation, often based on the properties of image pixels, is a widely used method in digital image processing and analysis to divide an image into multiple parts or areas. The main goal of image segmentation is to simplify the image for easier analysis. It would be very difficult to implement computer vision without performing image segmentation. An important component of computer vision is image segmentation, which has numerous commercial applications. Google and others Image-based search engines use image segmentation algorithms to identify the objects in your image and match their results to the relevant images they find to present you with search results.

DOI

10.21608/aujst.2023.183546.1012

Keywords

Image Segmentation, Optimization algorithms, Hybrid optimization algorithms

Authors

First Name

Ashraf

Last Name

Hemeida

MiddleName

Mohamed

Affiliation

Department of Electrical Engineering, Faculty of Energy Engineering

Email

ashraf@aswu.edu.eg

City

-

Orcid

-

First Name

Heba

Last Name

Yahya

MiddleName

GamalEldeen

Affiliation

Department of Mathematics, Faculty of Sciences, Aswan University

Email

hgamal799@gmail.com

City

-

Orcid

-

First Name

Hamida

Last Name

Al-Sanary

MiddleName

-

Affiliation

Department of Mathematics, Faculty of Sciences, Aswan University

Email

nour42387@gmail.com

City

-

Orcid

-

Volume

2

Article Issue

2

Related Issue

38033

Issue Date

2022-12-01

Receive Date

2022-12-26

Publish Date

2022-12-01

Page Start

86

Page End

104

Print ISSN

2735-3087

Online ISSN

2735-3095

Link

https://aujst.journals.ekb.eg/article_278978.html

Detail API

https://aujst.journals.ekb.eg/service?article_code=278978

Order

278,978

Type

Review papers

Type Code

2,313

Publication Type

Journal

Publication Title

Aswan University Journal of Sciences and Technology

Publication Link

https://aujst.journals.ekb.eg/

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Details

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Article

Created At

23 Jan 2023