Image Segmentation Using Fuzzy Clustering

This article explores the process of image segmentation using fuzzy clustering techniques. Fuzzy clustering serves as a prevalent image segmentation methodology that identifies distinct image regions by grouping pixels based on similarity measures. We will implement this approach using MATLAB programming language, demonstrating how to leverage MATLAB's built-in fuzzy clustering algorithms for effective image segmentation. The implementation covers critical aspects including selection of appropriate clustering algorithms (such as FCM - Fuzzy C-Means) and parameters, image preprocessing techniques for optimal results, and quantitative evaluation methods for assessing segmentation accuracy. Key MATLAB functions like fcm() for fuzzy clustering operations and imread() for image loading will be discussed with implementation examples. Through this article, you will gain practical knowledge of applying fuzzy clustering for image segmentation while developing fundamental proficiency in MATLAB programming for computer vision applications.