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Fuzzy “Along” Spatial Relation in 3D. Application to Anatomical Structures in Maxillofacial CBCT

Abstract : Spatial relations have proved to be of great importance in computer vision and image understanding. One issue is their modeling in the image domain, hence allowing for their integration in segmentation and recognition algorithms. In this paper, we focus on the “along” spatial relation. Based on a previous work that considered its modeling in 2D, we propose several extensions to 3D. More precisely, starting from the inter-objects region, we demonstrate that the elongation of the interface between the objects and this region gives a good evaluation of the alongness degree. We also integrate distance information to take into account only parts of the objects that are close to each other. Since fuzziness is well suited to model vagueness, we also describe how to define the alongness relation within the fuzzy set theory. Our method gives a quantitative satisfaction degree of the relation, reliable for differentiating spatial situations. An original example on the maxillofacial area in Cone-Beam Computed Tomography (CBCT) illustrates how the proposed approach could be used to recognize elongated structures.
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Submitted on : Saturday, September 14, 2019 - 6:49:05 PM
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  • HAL Id : hal-02288440, version 1



Timothée Evain, Xavier Ripoche, J. Atif, Isabelle Bloch. Fuzzy “Along” Spatial Relation in 3D. Application to Anatomical Structures in Maxillofacial CBCT. 18th International Conference on Image Analysis and Processing (ICIAP), 2015, Genova, Italy. pp.271-281. ⟨hal-02288440⟩



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