An Iterative Spanning Forest Framework for Superpixel Segmentation

• Published in: IEEE transactions on image processing Vol. 28; no. 7; pp. 3477 - 3489
• Main Authors: Vargas-Munoz, John E., Chowdhury, Ananda S., Alexandre, Eduardo B., Galvao, Felipe L., Vechiatto Miranda, Paulo A., Falcao, Alexandre X.
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.07.2019; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Computer science; Computer vision; connectivity function; Convergence; Datasets; Forestry; Graph theory; Image color analysis; Image foresting transform; Image processing; Image segmentation; Information systems; Iterative methods; mixed seed sampling; Seeds; spanning forests; superpixel/supervoxel segmentation; Vegetation

Superpixel segmentation has emerged as an important research problem in the areas of image processing and computer vision. In this paper, we propose a framework, namely Iterative Spanning Forest (ISF), in which improved sets of connected superpixels (supervoxels in 3D) can be generated by a sequence...