Research On Methods Of Improving Perform Of Content-based Image Retrieval System

With the development of the technology of the network, multimedia, database and mass storage, the quantity of digital image is increasing continuously, used extensively day by day, and digital images become one of the main information resources in the information society. Without the automatic and effective description about the image and the vision, a large amount of information would be flooded in information ocean, and unable to be searched out while needing. So, how to organize, express, store, manage, search and retrieval the giant digital images has been a very active research field all the time since the 1990's.However, because images possess abundant semantic information and complicated vision features, it is difficult to set up relations between semantic information and corresponding vision features of the multimedia target in present computer vision technology, which leads to the Content-Based Image Retrieval (CBIR) to be difficult to fulfill the request for practical application at accuracy of retrieval.In order to overcome the defect in CBIR system, this dissertation studies the methods to improve CBIR system performance, and then gives an experiment to prove and appraise the conclusions through an experiment.The dissertation is divided into 5 parts:The first part expatiates on the image retrieval mode and its characteristics, introduces the typical system of the image retrieval and its application field.The second part describes the key technology of CBIR, mainly including the extraction and expression of the image features, the image similarity measure technology, the decreasing and indexing of image high-dimensional-feature, and evaluating of CBIR' performance.The third part introduces the improving methods of the CBIR system, mainly including clustering technology., multi-feature retrieval, and the relevance feedback technology .The fourth part discusses about realizing of CBIR system based on relevance feedback, introducing algorithms of relevance feedback and the construction of CBIR system on the basis of relevance feedback.The last part proved effectiveness of CBIR system based on relevance feedback technology through an experiment.