Abstract
We propose a quantitative evaluation of morphological hierarchies (quasi-flat zones, constraint connectivity, watersheds, observation scale) in a novel framework based on the marked segmentation problem. We created a set of automatically generated markers for the one object image datasets of Grabcut and Weizmann. In order to evaluate the hierarchies, we applied the same segmentation strategy by combining several parameters and markers. Our results, which shows important differences among the considered hierarchies, give clues to understand the behaviour of each method in order to choose the best one for a given application. The code and the marker datasets are available online.
This work received funding from ANR (ANR-2010-BLAN-0205-03), CAPES/PVE under Grant 064965/2014-01, and CAPES/COFECUB under Grant 592/08.
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Perret, B., Cousty, J., Ura, J.C.R., Guimarães, S.J.F. (2015). Evaluation of Morphological Hierarchies for Supervised Segmentation. In: Benediktsson, J., Chanussot, J., Najman, L., Talbot, H. (eds) Mathematical Morphology and Its Applications to Signal and Image Processing. ISMM 2015. Lecture Notes in Computer Science(), vol 9082. Springer, Cham. https://doi.org/10.1007/978-3-319-18720-4_4
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DOI: https://doi.org/10.1007/978-3-319-18720-4_4
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