On Building a Hierarchical Region-Based Representation for Generic Image Analysis

Abstract

This paper studies the procedure to create a hierarchical region-based image representation aiming at generic image analysis. This study is carried out in the context of bottom-up segmentation algorithms and, specifically, using the Binary Partition Tree implementation. The different steps necessary to create a hierarchical region-based representation are analyzed; namely, (i) the creation of the initial partition in the hierarchy, which is split into the definition of the initial merging criterion and the proposal of a stopping criterion, and (ii) the merging criteria used to produce the different regions in the final hierarchical representation. For both steps, the proposed approach is assessed and compared with previous existing ones over a large data set using well-established partition-based metrics.