In order to utilize the large volume of images in databases efficiently, content-based image retrieval (CBIR) has been successfully employed whereby instead of the actual images extracted feature descriptors are used. CBIR systems usually employ multidimensional indexing structures, such as the R*tree or the SR-tree to index these features and thus to speed-up the query performance. However, th...

In this chapter, we present a basic introduction of the two very important areas of research in the domain of information technology, namely, multimedia systems and content-based image retrieval. The latter is still a widely unresolved problem. We discuss some of the works done so far in content-based image retrieval in the context of multimedia systems.

The paper discusses the role of invariance in content-based image retrieval, and discusses future directions.

For content based image retrieval using shape descriptors, most approaches so far extract shape information from a segmentation of the image. Shape features derived based on a specific segmentation are not suitable for images containing complex structures. Further, static segmentation based approaches are useful only for a small set of queries. In this paper we discuss the limitations of such b...

Dissimilarity measurement plays a crucial role in contentbased image retrieval, where data objects and queries are represented as vectors in high-dimensional content feature spaces. Given the large number of dissimilarity measures that exist in many fields, a crucial research question arises: Is there a dependency, if yes, what is the dependency, of a dissimilarity measure’s retrieval performan...

Modeling the characteristics of specific images and individual users is a critical issue in content-based image retrieval but insufficiently addressed by the current retrieval approaches. In this paper, we propose a novel approach to dataadaptive and user-adaptive image retrieval based on the idea of peer indexing—describing an image through semantically relevant peer images. Specifically, we a...