Adaptive Fuzzy C-Means Clustering Algorithm on Level Set Method for Noisy Images

Authors

  • Saikumar T Sr. Asst. Prof, Dept of ECE, CMR Technical Campus, Hyderabad, India.
  • Shashidhar B Associate Professor, Dept of Mathematics, GNITC, Hyderabad, India

Keywords:

Image segmentation, AFCM, level set method, images

Abstract

In this paper, Adaptive fuzzy c-means (AFCM) was used to generate an initial contour curve which overcomes leaking at the boundary during the curve propagation. Firstly, AFCM algorithm computes the fuzzy membership values for each pixel. On the basis of AFCM the edge indicator function was redefined. Using the edge indicator function the segmentation of medical images which are added with salt and pepper noise was performed to extract the regions of interest for further processing. The results of the above process of segmentation showed a considerable improvement in the evolution of the level set function.

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Published

2024-02-27

How to Cite

Saikumar, T., & Shashidhar, B. (2024). Adaptive Fuzzy C-Means Clustering Algorithm on Level Set Method for Noisy Images. COMPUSOFT: An International Journal of Advanced Computer Technology, 2(08). Retrieved from https://ijact.in/index.php/j/article/view/45

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Original Research Article

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