Seed robustness of oriented image foresting transform: Core computation and the robustness coefficient

Abstract

In graph-based methods, image segmentation can be seen as a graph partition problem between sets of seed pixels. The core of a seed is the region where it can be moved without altering its segmentation. The larger the core, the greater the robustness of the method in relation to its seed positioning. In this work, we present an algorithm to compute the cores of Oriented Image Foresting Transform (OIFT), an extension of Fuzzy Connectedness and Watersheds to directed weighted graphs, and compare its performance to other methods according to a proposed evaluation measure, the Robustness Coefficient. Our analysis indicates that OIFT has a good balance between accuracy and robustness, being able to overcome several methods in some datasets.