Скачать или смотреть Color Image Segmentation System Based on MATLAB Clustering

This study designed and implemented a color image clustering segmentation system based on MATLAB GUI, integrating three typical unsupervised clustering algorithms: K-means, Fuzzy C-Means (FCM), and Bisecting K-means. The system features a user-friendly interface and simple operations, enabling image import, parameter setting, algorithm selection, and result visualization. Experimental results show that each clustering method performs differently on various images: K-means offers fast computation suitable for quick processing tasks; FCM produces smooth boundaries, ideal for images requiring high segmentation accuracy; and Bisecting K-means achieves higher efficiency while maintaining good segmentation quality, making it suitable for large-scale image data. Overall, the system provides a practical and extensible platform for teaching, comparing, and researching image segmentation algorithms.