Image segmentation through combined methods : watershed transform, unsupervised distance learning and normalized cut

Image segmentation through combined methods : watershed transform, unsupervised distance learning and normalized cut

Tiago W. Pinto, Marco A. G. de Carvalho, Daniel C. G. Pedronette, Paulo S. Martins

ARTIGO

Inglês

Research on image processing has shown that combining segmentation methods may lead to a solid approach to extract semantic information from different sort of images. Within this context, the Normalized Cut (NCut) is usually used as a final partitioning t

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Fechado

Image segmentation through combined methods : watershed transform, unsupervised distance learning and normalized cut

Tiago W. Pinto, Marco A. G. de Carvalho, Daniel C. G. Pedronette, Paulo S. Martins


										

Image segmentation through combined methods : watershed transform, unsupervised distance learning and normalized cut

Tiago W. Pinto, Marco A. G. de Carvalho, Daniel C. G. Pedronette, Paulo S. Martins

    Fontes

    2014 Southwest Symposium on Image Analysis and Interpretation

    (May, 2014), p. 153-156, n. art. 6806052