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Abstract : In this article, we present a fast-marching based algorithm for generating superpixel (FMS) partitions of images. The idea behind the algorithm is to draw an analogy between waves propagating in an heterogeneous medium and regions growing on an image at a rate depending on the local color and texture. The FMS algorithm is evaluated on the Berkeley Segmentation Dataset 500. It yields results in term of boundary adherence that are comparable to the ones obtained with state of the art algorithms including SLIC or ERGC, while improving on these algorithms in terms of compactness and density.
https://hal.archives-ouvertes.fr/hal-03105868 Contributor : Bruno FigliuzziConnect in order to contact the contributor Submitted on : Monday, January 11, 2021 - 2:09:49 PM Last modification on : Wednesday, November 17, 2021 - 12:27:19 PM
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Distributed under a Creative Commons Attribution 4.0 International License
Kaiwen Chang, Bruno Figliuzzi. Fast marching based superpixels. Mathematical Morphology - Theory and Applications, De Gruyter 2020, 4 (1), pp.127-142. ⟨10.1515/mathm-2020-0105⟩. ⟨hal-03105868⟩