We study a notion of variation for real valued two variable functions called the path variation and we discuss its application as a low-level image segmentation method. For this purpose, we characterize the path variation as an energy in the framework of minimal paths. In this context, the definition of an energy and the selection of a set of source points determine a partition of the image domain. The problem of choosing a relevant set of sources is addressed through a nonlinear diffusion filtering. © Springer-Verlag Berlin Heidelberg 2003.
CITATION STYLE
Arbeláez, P. A., & Cohen, L. D. (2003). Path variation and image segmentation. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2683, 246–260. https://doi.org/10.1007/978-3-540-45063-4_16
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