MUVIS: a system for content-based indexing and retrieval in large image databases

Until recently, collections of digital images were stored in classical databases and indexed by keywords entered by a human operator. This is not longer practical, due to the growing size of these collections. Moreover, the keywords associated with an image are either selected from a fixed set of words and thus cannot cover the content of all images; or they are the operators' personal description of each image and, therefore, are subjective. That is why systems for image indexing based on their content are needed. In this context, we propose in this paper a new system, MUVIS*, for content-based indexing and retrieval for image database management systems. MUVIS*indexes by key words, and also allows indexing of objects and images based on color, texture, shape and objects' layout inside them. Due to the use of large vector features, we adopted the pyramid trees are used for creating the index structure. The block diagram of the system is presented and the functionality of each block is explained. The features used are presented as well.