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

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.

Mots clés: Stochastic watershed; Mathematical Morphology; Probabilistic segmentation; Regionalized random markers; Image segmentation; Multivariate image analysis; Hyperspectral image analysis; Watershed algorithm; Probabilistic watershed; Angiogenesis image segmentation

Domaines: Mathématiques appliquées; Traitement d'image; Probabilités [math.PR]; Matériaux; Traitement du signal et de l'image [eess.SP]

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⟩