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In this paper, we propose and compare two supervised algorithms for the segmentation of textured sonar images, with respect to seafloor types. We characterize seafloors by a set of empirical distributions estimated on texture responses to a set of different filters. Moreover, we introduce a novel similarity measure between sonar textures in this feature space. Our similarity measure is defined as...
We propose a region-based segmentation of textured sonar images within a level set framework. We state image segmentation as the minimization of an energy involving region regularity constraints and a texture similarity measure adapted to sonar images (introduced in our previous work [Karoui, I., et al., 2005]). In this framework, sonar textures are characterized by statistics of their responses to...
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