M. Lalitha, M. Kiruthiga, C. Loganathan
Abstract: The goal of this survey on different clustering techniques is to achieve image segmentation. Clustering can be termed here as a grouping of similar images. The purpose of clustering is to get meaningful result, effective storage and fast retrieval in various areas. The goal is to provide a self-contained review of the concepts and the mathematics underlying clustering techniques. Then the clustering methods are presented, divided into: hierarchical, partitioning, density-based, model-based, grid-based, and soft-computing methods. The goal of this survey is to provide a comprehensive review of different clustering and image segmentation techniques. Due to the importance of image segmentation and clustering a number of algorithms have been proposed but based on the image that is inputted the algorithm should be chosen to get the best results.
Keywords: Clustering, Image segmentation, Hierarchical, K-means, Spectral Clustering, Histogram-based