Scale Space Exploration for Mining Image Information Content

Abstract

In this paper, we describe an application of a scalespace clustering algorithm (melting) for exploration of image information content. Clustering by melting considers the feature space as a thermodynamical ensemble and groups the data by minimizing the free energy, having the temperature as a scale parameter. We develop clustering by melting for multidimensional data, and propose and demonstrate a solution for the initialization of the algorithm. processes of analyzing data from different perspectives and summarizing it into useful information.