Classification-Driven Stochastic Watershed: Application to Multispectral Segmentation

Abstract : The aim of this paper is to present a general methodology based on multispectral mathematical morphology in order to segment multispectral images. The methods consists in computing a probability density function pdf of contours conditioned by a spectral classification. The pdf is conditioned through regionalized random balls markers thanks to a new algorithm. Therefore the pdf contains spatial and spectral information. Finally, the pdf is segmented by a watershed with seeds (i.e., markers) coming from the classification. Consequently, a complete method, based on a classification-driven stochastic watershed is introduced. This approach requires a unique and robust parameter: the number of classes which is the same for similar images. Moreover, an efficient way to select factor axes, of Factor Correspondence Analysis (FCA), based on signal-to-noise ratio on factor pixels is presented.
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Communication dans un congrès
CGIV 2008/MCS'08 4th European Conference on Colour in Graphics, Imaging, and Vision and 10th International Symposium on Multispectral Colour Science, Jun 2008, Terrassa - Barcelona, Spain. Society for Imaging Science and Technology, pp.471-476, 2008, Conference on Colour in Graphics, Imaging, and Vision, CGIV 2008. 〈http://www.ingentaconnect.com/contentone/ist/cgiv/2008/00002008/00000001/art00101〉
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Soumis le : lundi 13 mars 2017 - 14:39:02
Dernière modification le : vendredi 27 octobre 2017 - 17:36:02
Document(s) archivé(s) le : mercredi 14 juin 2017 - 13:41:42

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Guillaume Noyel, Jesus Angulo, Dominique Jeulin. Classification-Driven Stochastic Watershed: Application to Multispectral Segmentation. CGIV 2008/MCS'08 4th European Conference on Colour in Graphics, Imaging, and Vision and 10th International Symposium on Multispectral Colour Science, Jun 2008, Terrassa - Barcelona, Spain. Society for Imaging Science and Technology, pp.471-476, 2008, Conference on Colour in Graphics, Imaging, and Vision, CGIV 2008. 〈http://www.ingentaconnect.com/contentone/ist/cgiv/2008/00002008/00000001/art00101〉. 〈hal-00830667〉

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