Supervised tree content based search algorithm for multimedia image databases

Abstract

For indexing an image databases there are used many features. In this paper are used features like histograms for the color components, stochastic moments, few parameters of the co-occurrences matrix and the Gabor filters decomposition. Using all of them we obtain good performance in the field of content-based image indexing and retrieval. There are some speed problems because are many features used in the search process. Here, I present an algorithm for indexing and retrieval, which use a supervised tree algorithm for speed increasing. The area of applications is very wide: multimedia documents, transaction systems, medical application.