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Article Details

Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

Image Enhancement Method based on an Improved Fuzzy C-Means Clustering

Author 1: Libao Yang
Author 2: Suzelawati Zenian
Author 3: Rozaimi Zakaria

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Digital Object Identifier (DOI) : 10.14569/IJACSA.2022.0130899

Article Published in International Journal of Advanced Computer Science and Applications(IJACSA), Volume 13 Issue 8, 2022.

  • Abstract and Keywords
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Abstract: Image enhancement is an important method in the process of image processing. This paper proposes an image enhancement method base on an improved fuzzy c-means clustering. The method consists of the following steps: firstly, proposed a fuzzy c-means clustering with a cooperation center(FCM-co). Secondly, using the FCM-co, divide the image pixels into different clusters and marked membership values to those clusters. Thirdly, modify the membership values. Finally, calculate the new pixel gray levels. This enhancement method can overcome the disadvantage of overexposure and better retain image details. Through the experiment, the test results show that the proposed enhancement method could achieve better performance.

Keywords: Image enhancement; fuzzy clustering; fuzzy c-means clustering; membership; objective function

Libao Yang, Suzelawati Zenian and Rozaimi Zakaria, “Image Enhancement Method based on an Improved Fuzzy C-Means Clustering” International Journal of Advanced Computer Science and Applications(IJACSA), 13(8), 2022. http://dx.doi.org/10.14569/IJACSA.2022.0130899

@article{Yang2022,
title = {Image Enhancement Method based on an Improved Fuzzy C-Means Clustering},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2022.0130899},
url = {http://dx.doi.org/10.14569/IJACSA.2022.0130899},
year = {2022},
publisher = {The Science and Information Organization},
volume = {13},
number = {8},
author = {Libao Yang and Suzelawati Zenian and Rozaimi Zakaria}
}


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