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Conference papers

Stochastic Multiscale Segmentation Constrained by Image Content

Abstract : We introduce a noise-tolerant segmentation algorithm efficient on 3D multiscale granular materials. The approach uses a graph-based version of the stochastic watershed and relies on the morphological granulometry of the image to achieve a content-driven unsupervised segmentation. We present results on both a virtual material and a real X-ray microtomographic image of solid propellant.
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Contributor : Luc Gillibert Connect in order to contact the contributor
Submitted on : Thursday, March 17, 2011 - 2:11:13 PM
Last modification on : Wednesday, November 17, 2021 - 12:27:12 PM
Long-term archiving on: : Thursday, November 8, 2012 - 12:05:15 PM


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Luc Gillibert, Dominique Jeulin. Stochastic Multiscale Segmentation Constrained by Image Content. 10th International Symposium on Mathematical Morphology and Its Application to Signal and Image Processing, ISMM 2011, Jul 2011, Verbania-Intra, Italy. pp.132-142, ⟨10.1007/978-3-642-21569-8_12⟩. ⟨hal-00577776⟩



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