2023
DOI: 10.1088/2631-8695/acffa7
|View full text |Cite
|
Sign up to set email alerts
|

Enhanced independent component analysis and fuzzy C-mean clustering based on novel bat algorithm for noisy image segmentation

Nabil Chetih,
Tawfik Thelaidjia,
Fatma Zohra Boudani

Abstract: Fuzzy c-means clustering is widely recognized as one of the most effective methods for image segmentation and achieving accurate classification. However, this method has two significant drawbacks: its sensitivity to noise and its convergence to local minimum clusters’ centroids. In this paper, we proposed a novel model called EIFCMNB, which incorporates enhanced independent component analysis (EICA), fuzzy c-means clustering (FCMC) and novel bat algorithm (NBA) for noise image segmentation. The suggested model… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

0
0
0

Year Published

2024
2024
2024
2024

Publication Types

Select...
1

Relationship

0
1

Authors

Journals

citations
Cited by 1 publication
references
References 38 publications
0
0
0
Order By: Relevance