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Modified Artificial Ecosystem-Based Optimization for Multilevel Thresholding Image Segmentation

Modified Artificial Ecosystem-Based Optimization for Multilevel Thresholding Image Segmentation

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_7b2f4ada602c4f78ab7984888bc3a62f

Modified Artificial Ecosystem-Based Optimization for Multilevel Thresholding Image Segmentation

About this item

Full title

Modified Artificial Ecosystem-Based Optimization for Multilevel Thresholding Image Segmentation

Publisher

Basel: MDPI AG

Journal title

Mathematics (Basel), 2021-10, Vol.9 (19), p.2363

Language

English

Formats

Publication information

Publisher

Basel: MDPI AG

More information

Scope and Contents

Contents

Multilevel thresholding is one of the most effective image segmentation methods, due to its efficiency and easy implementation. This study presents a new multilevel thresholding method based on a modified artificial ecosystem-based optimization (AEO). The differential evolution (DE) is applied to overcome the shortcomings of the original AEO. The m...

Alternative Titles

Full title

Modified Artificial Ecosystem-Based Optimization for Multilevel Thresholding Image Segmentation

Identifiers

Primary Identifiers

Record Identifier

TN_cdi_doaj_primary_oai_doaj_org_article_7b2f4ada602c4f78ab7984888bc3a62f

Permalink

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_7b2f4ada602c4f78ab7984888bc3a62f

Other Identifiers

ISSN

2227-7390

E-ISSN

2227-7390

DOI

10.3390/math9192363

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