Hierarchal Spatio-color Image Indexing and Retrieval Based on a Stochastic Model

In this paper, a hierarchal image indexing and retrieval technique is proposed. Both color distribution and spatial information in an image are incorporated to index images in a repository. A set of global and localized features are extracted for the image based on a stochastic model. A hierarchal approach is then used to index images based on the derived features. The reliability and robustness of the proposed technique against common intensity artifacts and noise is validated through several experiments conducted for that purpose. The proposed technique outperforms traditional and other histogram based techniques in terms of feature vector properties, as well as retrieval performance.