Performance Analysis of Content Based Video Retrieval System Using Clustering

the multimedia storage grows and the cost for storing multimedia data is cheaper. So there is huge number of videos available in the video repositories. It is difficult to retrieve the relevant videos from large video repository as per user in-terest as users shift from text based retrieval systems to content based retrieval systems. Video retrieval is very important in multimedia database management. This paper offers an overview of the landscape of general strategies in visual content-based video retrieval, focusing on methods for video structure analysis, including shot boundary detection, key frame extraction, extraction of features including static key frame features, object feature, video retrieval including similarity measures and the proposed procedure consists of the unique aspect of clustering techniques.