Research On Content-Based Image Retrieval

With the development of the technology of multimedia and internet, visual information is used more widely. As a result, effective methods of managing image databases and visual information are needed. As a key technique, Content-Based Image Retrieval(CBIR) has become one of the most active research areas in the past few years. This paper discusses the conception and methods of CBIR. Some future research trends are proposed also.CBIR is a process to search a certain image from the database by using some given visual characters. The key to implement the technique of CBIR is to extract features which present the content of image. So how to utilize the image process knowledge and visual technology to accomplish the management and retrieval of large image data with computers becomes a research focus.In the paper, a new image signature is computed for CBIR. The signature provides a compact description of all image aspects, including color and shape. Also the signature is invariant to 2D rigid transformation, such as rotation, scaling and translation. To improve the speed of image search, K-means Clustering is used to create the image database. Fuzzy clustering analysis is an important branch of fuzzy pattern recognition, it is an unsupervised pattern recognition method, and was widely used in many fields. In this paper, the application of suppressed fuzzy clustering algorithm in image segmentation is introduced.