Image Segmentation Using Fuzzy Clustering Algorithm
- Login to Download
- 1 Credits
Resource Overview
Detailed Documentation
This document explores image segmentation techniques with emphasis on fuzzy clustering algorithms. We present a MATLAB implementation of C-means clustering segmentation where users specify the desired number of segmentation classes. The algorithm processes input images through iterative cluster center optimization using membership functions to handle pixel classification uncertainties. Key implementation aspects include distance metric calculations (typically Euclidean), membership value updates, and centroid recomputation until convergence criteria are met. This approach significantly enhances image processing workflows by generating segmented images with improved contrast, enabling clearer observation of regional details and characteristics. The algorithm demonstrates particular effectiveness in handling overlapping regions and ambiguous boundaries through its probabilistic classification framework.
- Login to Download
- 1 Credits