Elucidating the Relations among Seeded Image Segmentation Methods and their Possible Extensions

Many image segmentation algorithms have been proposed, specially for the case of binary segmentation (object/background) in which hard constraints (seeds) are provided interactively. Recently, several theoretical efforts were made in an attempt to unify their presentation and clarify their relations. These relations are usually pointed out textually or depicted in the form of a table of parameters of a general energy formulation. In this work we introduce a more general diagram representation which captures the connections among the methods, by means of conventional relations from set theory. We formally instantiate several methods under this diagram, including graph cuts, power watersheds, fuzzy connectedness, grow cut, distance cuts, and others, which are usually presented as unrelated methods. The proposed diagram representation leads to a more elucidated view of the methods, being less restrictive than the tabular representation. It includes new relations among methods, besides bringing together the connections gathered from different works. It also points out some promising unexplored intermediate regions, which can lead to possible extensions of the existing methods. We also demonstrate one of such possible extensions, which is used to effectively combine the strengths of region and local contrast features.