The Research And Imlementation Of Key Technology Of Content-Based Image Retrieval

With the development of multimedia technology and the digital application, content-based image retrieval system has become the focus of multimedia retrieval research. It has bright market prospective and research potential, the efficiency of image retrieval will be improved significantly through the research of those key technologies.First, the background and meaning of content-based image retrieval is introduced in this thesis,which states the current image retrieval systems. Then it analysis the development status at home and abroad,through the analysis of those retrieval systems, it discusses the relative key technologies of content-based image retrieval.In view of the theoretical principle, this thesis depicts several key technologies involved in image retrieval in detail including the image feature description, such as color, texture and shape feature, and the image local features. In image local features, SIFT algorithm possesses the remarkable descriptive power and robustness, and gains generous applications. In order to overcome the semantic gap between low level feature and high level semantic, this thesis introduces the concept "visual words", after abstracting the SIFT feature, and it uses the clustering algorithm to generate image visual words and processes to the next step—“visual dictionary”. In the clustering procedure, this thesis uses the FCM algorithm and the common used K-means clustering algorithm, which gains more accurate results. As the FCM algorithm has more computation complexity, it’s calculation speed become lower. Meanwhile, in the clustering process, some image space information lost,and this thesis adopts the image pyramids algorithms to add space information, and finally get the image feature vectorspace visual word distribution density histogram. In the similarity measurement stage, this thesis uses the Histogram intersection method.In the last part, this paper tests the “SIFT+FCM+PYRAMID” algorithms on the image library, and proves effectiveness, then it analysis the simulation result and point out the future research direction.