MATLAB Implementation of C-Means Clustering Algorithm for Image Segmentation

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Resource Overview

A MATLAB-based implementation of the C-means clustering algorithm specifically designed for image segmentation, delivering excellent segmentation results with detailed code structure and algorithmic explanations

Detailed Documentation

This project presents a MATLAB implementation of the C-means clustering algorithm tailored for image segmentation applications. The implementation effectively partitions image pixels into clusters where pixels within the same cluster share similar characteristics. The algorithm employs an iterative optimization process that minimizes the within-cluster sum of squares, utilizing key MATLAB functions like kmeans() for cluster centroid computation and pdist2() for distance calculations between pixels and cluster centers. Through this clustering approach, distinct regions in the image are effectively separated, resulting in superior image processing outcomes. The code includes proper initialization of cluster centers, iterative reassignment of pixels to the nearest centroid, and convergence checking based on centroid stability thresholds.

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