Supplementary material for: An Iterative Spanning Forest Framework for Superpixel Segmentation

John E. Vargas-Munoz, Ananda S. Chowdhury, Eduardo B. Alexandre, Felipe L. Galvao, Paulo A. Vechiatto Miranda, Alexandre X. Falcao
2019 IEEE Transactions on Image Processing  
Superpixel segmentation has become an important research problem in image processing. In this paper, we propose an Iterative Spanning Forest (ISF) framework, based on sequences of Image Foresting Transforms, where one can choose i) a seed sampling strategy, ii) a connectivity function, iii) an adjacency relation, and iv) a seed pixel recomputation procedure to generate improved sets of connected superpixels (supervoxels in 3D) per iteration. The superpixels in ISF structurally correspond to
more » ... ning trees rooted at those seeds. We present five ISF methods to illustrate different choices of its components. These methods are compared with approaches from the state-of-the-art in effectiveness and efficiency. The experiments involve 2D and 3D datasets with distinct characteristics, and a high level application, named sky image segmentation. The theoretical properties of ISF are demonstrated in the supplementary material and the results show that some of its methods are competitive with or superior to the best baselines in effectiveness and efficiency.
doi:10.1109/tip.2019.2897941 fatcat:xfs3pzjernd4lhdfpok4hi63ky