Clustering is a common technique used in various fields like machine learning and bioinformatics. This study focuses on applying clustering to image data by categorizing it based on feature values. Different clustering algorithms are discussed, including partition-based, hierarchical-based, density-based, and grid-based algorithms. The study provides insights into the complexities of these methods and offers a detailed overview of how they work in data mining.