Image visualization based on MPEG-7 color descriptors

In this paper we address the user-navigation through large volumes of image data. A similarity-measure based on MPEG-7 color histograms is introduced and multidimensional scaling concepts are employed to display images in two dimensions according to their mutual similarities. With such a view the user can easily see relations and color similarity between images and understand the structure of the data base. In order to cope with large volumes of images a modified version of the k-means clustering technique is introduced which identifies representative image samples for each cluster. Representative images (up to 100) are then displayed in two dimensions using MDS structuring. The modified clustering technique proposed produces a hierarchical structure of clusters similar to street maps with various resolutions of detail. The user can zoom into various cluster levels to obtain more or less detail if required. The results obtained verify the attractiveness of the approach for navigation and retrieval applications.