L1 Patch-based image partitioning into homogeneous textured regions

Oliver, Maria; Haro Ortega, Gloria; Fedorov, Vadim; Ballester, Coloma

doi:http://dx.doi.org/10.1109/ICASSP.2018.8462594

L1 Patch-based image partitioning into homogeneous textured regions

Citation

Oliver M, Haro G, Fedorov V, Ballester C. L1 Patch-based image partitioning into homogeneous textured regions. In: 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP); 2018 Apr 15-20; Calgary, Canada. Piscataway: IEEE; 2018. p. 1558-62. DOI: 10.1109/ICASSP.2018.8462594

Abstract

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.

Description

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.