Browsing an image database utilizing the associations between images and features

In this paper the associations between the low-level features and the images are utilized to create a visualization that enables the user to determine the nature of the database, e.g., what are the predominant features for a group of images and vice-versa. This is based on modeling the database with a bipartite graph and partitioning the graph to find partitions of images and low-level features. Moreover, by using the concept of orthogonal arrays, a sample of images from each partition are presented to the user as a visual snapshot of the database.