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BY-NC-ND 3.0 license Open Access Published by De Gruyter Open Access December 30, 2016

Morphological probabilistic hierarchies for texture segmentation

  • Dominique Jeulin

Abstract

A general methodology is introduced for texture segmentation in binary, scalar, or multispectral images. Textural information is obtained from morphological operations on images. Starting from a fine partition of the image in regions, hierarchical segmentations are designed in a probabilistic framework by means of probabilistic distances conveying the textural or morphological information, and of random markers accounting for the morphological content of the regions and of their spatial arrangement. The probabilistic hierarchies are built from binary or multiple fusion of regions.

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Received: 2016-7-20
Accepted: 2016-2-11
Published Online: 2016-12-30

© 2016 Dominique Jeulin

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

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