Cargando…
Improvement in the Between-Class Variance Based on Lognormal Distribution for Accurate Image Segmentation
There are various distributions of image histograms where regions form symmetrically or asymmetrically based on the frequency of the intensity levels inside the image. In pure image processing, the process of optimal thresholding tends to accurately separate each region in the image histogram to obt...
Autores principales: | Jumiawi, Walaa Ali H., El-Zaart, Ali |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9497484/ https://www.ncbi.nlm.nih.gov/pubmed/36141093 http://dx.doi.org/10.3390/e24091204 |
Ejemplares similares
-
Improving Minimum Cross-Entropy Thresholding for Segmentation of Infected Foregrounds in Medical Images Based on Mean Filters Approaches
por: Jumiawi, Walaa Ali H., et al.
Publicado: (2022) -
A Boosted Minimum Cross Entropy Thresholding for Medical Images Segmentation Based on Heterogeneous Mean Filters Approaches
por: Jumiawi, Walaa Ali H., et al.
Publicado: (2022) -
Human lipoproteins comprise at least 12 different classes that are lognormally distributed
por: Konishi, Tomokazu, et al.
Publicado: (2022) -
An Optimized Approach for Prostate Image Segmentation Using K-Means Clustering Algorithm with Elbow Method
por: Sammouda, Rachid, et al.
Publicado: (2021) -
Improving the segmentation of digital images by using a modified Otsu’s between-class variance
por: Singh, Simrandeep, et al.
Publicado: (2023)