Perception-Based Image Segmentation Using the Bounded Irregular Pyramid.

This paper presents a bottom-up approach for fast segmentation of natural images. This approach has two main stages: firstly, it detects the homogeneous regions of the input image using a colour-based distance and then, it merges these regions using a more complex distance. Basically, this distance complements a contrast measure defined between regions with internal region descriptors and with attributes of the shared boundary. These two stages are performed over the same hierarchical framework: the Bounded Irregular Pyramid (BIP). The performance of the proposed algorithm has been quantitatively evaluated with respect to ground-truth segmentation data. [ABSTRACT FROM AUTHOR]