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Conference Papers Year : 2015

Convex Color Image Segmentation with Optimal Transport Distances

Julien Rabin

Abstract

This work is about the use of regularized optimal-transport distances for convex, histogram-based image segmentation. In the considered framework, fixed exemplar histograms define a prior on the statistical features of the two regions in competition. In this paper, we investigate the use of various transport-based cost functions as discrepancy measures and rely on a primal-dual algorithm to solve the obtained convex optimization problem.
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Dates and versions

hal-01133447 , version 1 (19-03-2015)

Identifiers

  • HAL Id : hal-01133447 , version 1

Cite

Julien Rabin, Nicolas Papadakis. Convex Color Image Segmentation with Optimal Transport Distances. International Conference on Scale Space and Variational Methods in Computer Vision (SSVM'15), May 2015, Lège Cap Ferret, France. pp.256-269. ⟨hal-01133447⟩
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