LITERATURE SURVEY ON VARIOUS CLUSTERING TECHNIQUES USING VIDEO DATA IMAGE

The amount of information produced every year is rapidly growing due to many factor among all media, video is a particular media embedding visual, motion, audio and textual information. Given this huge amount of information the researchers need effective c lustering techniques for the video data. The similarity is obtained from the attribute values of the objects. The basic attributes are distance, pixel value, and other common factor if any. The goal of this research 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 and grid - based methods. The goal of this survey is to provide a comprehensive rev iew of different clustering techniques. Due to the importance of 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.