The Study Of Technique On Content-Based Image Retrieval

Demand for effectively managing the huge amount of image data becomes more and More urgent, because traditional retrieval methods based on keyword and description text are not competent for it while resources of images and videos becomes more and more abundant in modern information era. Content based image and video retrieval techniques have emerged as the times require, which combine the multi-disciplinary such as image understanding, computer vision, database technique and artificial intelligence etc, It has many advanced aspects such as objective and flexible description, highly automatic input process and wide application areas etc, which has been paid more and more attentions and developed rapidly .In this dissertation, content based retrieval techniques for a static image is deeply researched, and some valuable results are achieved based on a thorough investigation of the current techniques.Firstly, the application of fuzzy theory in CBIR is researched elementarily, a method based on fuzzy color histogram of the image is carried out, and some analysis and discussion are done about the experiment results. Secondly, the retrieval method based on color feature is analyzed detailed, and two improved methods based on the object in the image are presented. By comparing with general color method, the improvement of retrieval efficiency is proved. A method using combined color and texture features is also given and compared with which using single feature. Thirdly, an emphasized research is focused on the appliance of relevance feedback in CBIR, and an improve method based on the relevance of the users is given. With plentiful experiments it is proved that the retrieval efficiency can be enhanced greatly by using this method.