Automatic Superpixel-Based Clustering for Color Image Segmentation Using q-Generalized Pareto Distribution under Linear Normalization and Hunger Games Search

Automatic Superpixel-Based Clustering for Color Image Segmentation Using q-Generalized Pareto Distribution under Linear Normalization and Hunger Games Search

Superixel is one of the most efficient of the image segmentation approaches that are widely used for different applications. In this paper, we developed an image segmentation based on superpixel and an automatic clustering using q-Generalized Pareto distribution under linear normalization (q-GPDL),...

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Bibliographic Details
Main Authors: Mohamed Abd Elaziz, Esraa Osama Abo Zaid, Mohammed A. A. Al-qaness, Rehab Ali Ibrahim
Format: Article
Language:English
Published: MDPI AG 2021-09-01
Series:Mathematics
Subjects:
superpixel
image segmentation
hunger games search (HGS)
density peaks clustering
q-generalized pareto distribution under linear normalization (q-GPDL)
Online Access:https://www.mdpi.com/2227-7390/9/19/2383

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https://www.mdpi.com/2227-7390/9/19/2383

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