Research And Implementation Of Optimization For Coalition Based Image Retrieval

With the emergence of the large-scale digital image database, the traditional reliance on artificial mark the text-based image retrieval technology has been unable to meet the growing requirements of users, so content-based image retrieval technology (Content-based image retrieval CBIR) appears. Generally, CBIR extracts certain features of images; its characteristics pose a vector, to facilitate the retrieval of the feature space index. Now there are different ways of indexing, CM-tree (clustered metric tree) is a relatively new approach.The nodes of CM-tree preserve the clustered radius and the distance tables of clusters, the range query algorithm based on clustered metric speed up the retrieval time by using the distance tables'information, according to the number of calculation reduced by the triangle inequality. The retrieval based on clustered metric have certain advantages when dealing with single query and query of small amount data. However, the queries submitted by users in a certain period of time have considerable relevance, extremely, they're repetitive. Much have to be done if conventional retrieval method is still adopted, such as retrieval a same picture repeatedly, or retrieval quite related pictures for many times. The optimization method of clustered metric based on coalition can solve the above problem.Coalition is a technical means that a main query and certain invited queries form a new compound query by using some rules. The application layer of coalition is under the root node, the main query invites other queries and conduct coalition operations with certain rules in different navigation nodes of the level, then create a new compound query and retrieval it in the corresponding navigation node. At the same time, the attributes in the main query and the invited queries keep the coalition information, the invited queries need not retrieval in the nodes which keep the coalition information during the next retrieval process, and the operations can avoid retrieving repeatedly, reduce the retrieval times, so it can improve the efficiency of retrieval. The optimization for clustered metric retrieval based on coalition mainly used in the condition of real-time query context. The experiment proved that the usage of technology can greatly improve the efficiency of retrieval.