Content-based Image Information Retrieval Systems

As an interdisciplinary field, content-based image retrieval combines the efforts of computer vision, pattern recognition, database management sysytem, artificial intelligence, etc, together. In today's digital society, the explosive growth of image data has far outpaced the ability of exsiting systems to retrieve it. The tools and techniques are needed to meet users' require of information.In this paper, we describe color feature space aiming to query by color content. Meanwhile, we evaluate several transformations and quantizitions of color. Then we propose a method of color image representation to facilitate color region retrival, an approach named generalized R- tree to enhance image searching efficience.Deformable template matching is a useful method in the fields such as shape-based image information query and pattern recognition. In order to overcome the shortcomings of template structure, energy formula and deformation method about ordinary template matching, we present a more reasonable template structure, simplify the inner-energy formula of the template, and propose the conception of quasi-similarity for the planar shape so that the template deformation has some psychological foundation. An algorithm of shape-based query of image information using deformable template is also given.The previous query languages, in particular, aim at structural data in traditional applications. A query language, CISQL, is proposed and defined which is both intuitive and expressive to specify constraints for image object. The objectives are to support content-based retrieval by prominent feature regions, spatial information and similarity measures from various examples. Conseuqently, the search operators can be applied to obtain results.The most challenging task is to establish a framework which is both extensible and scalable Existing systems can be scalable if the retrieval is...