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Regionalized Random Germs by a Classification for Probabilistic Watershed Application: Angiogenesis Imaging Segmentation

Guillaume Noyel 1 Jesus Angulo 1 Dominique Jeulin 1
1 CMM - Centre de Morphologie Mathématique
Abstract : New methods are presented to generate random germs regionalized by a previous classification in order to use probabilistic watershed on hyperspectral images. These germs are much more efficient than the standard uniform random germs.
Keywords : Angiogenesis image segmentation Multivariate image analysis Hyperspectral image analysis Watershed algorithm Probabilistic watershed Regionalized random markers Image segmentation Probabilistic segmentation Stochastic watershed Mathematical Morphology
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Submitted on : Saturday, June 15, 2013 - 10:32:43 AM
Last modification on : Thursday, September 24, 2020 - 4:38:03 PM
Long-term archiving on: : Monday, September 16, 2013 - 4:04:00 AM

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Guillaume Noyel, Jesus Angulo, Dominique Jeulin. Regionalized Random Germs by a Classification for Probabilistic Watershed Application: Angiogenesis Imaging Segmentation. Alistair D. Fitt, John Norbury, Hilary Ockendon, and Eddie Wilson. Progress in Industrial Mathematics at ECMI 2008, Springer, pp.211-216, 2010, Mathematics in Industry, 978-3-642-12109-8. ⟨10.1007/978-3-642-12110-4_29⟩. ⟨hal-00834452⟩

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