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Título:
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L1 Patch-based image partitioning into homogeneous textured regions
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Autor/a:
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Oliver, Maria; Haro Ortega, Gloria; Fedorov, Vadim; Ballester, Coloma
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Abstract:
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Comunicació presentada al congrés International Conference on Acoustics, Speech and Signal Processing (ICASSP) celebrat a Calgary (Canadà) del 15 al 20 d'abril de 2018. |
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Abstract:
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This paper proposes a novel patch-based variational segmentation method that considers adaptive patches to characterize, in an affine invariant way, the local structure of each homogeneous texture region of the image and thus being capable of grouping the same kind of texture regardless of differences in the point of view or suffered perspective distortion. The patches are computed using an affine covariant structure tensor defined at every pixel of the image domain, so that they can automatically adapt its shape and size. They are used in a segmentation model that uses an L 1 -norm fidelity term and fuzzy membership functions, which is solved by an alternating scheme. The output of the method is a partition of the image in regions with homogeneous texture together with a patch representative of the texture of each region. |
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Materia(s):
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-Image segmentation
-Variational methods
-L1-fidelity
-Patch-based methods
-Affine invariant patch similarity |
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Derechos:
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© 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
The final published article can be found at https://ieeexplore.ieee.org/document/8462594
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Tipo de documento:
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Objeto de conferencia
Artículo - Versión aceptada |
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Editor:
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Institute of Electrical and Electronics Engineers (IEEE)
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