How to Make nD Images Well-Composed Without Interpolation
From LRDE
- Authors
- Nicolas Boutry, Thierry Géraud, Laurent Najman
- Where
- Proceedings of the IEEE International Conference on Image Processing (ICIP)
- Place
- Québec City, Canada
- Type
- inproceedings
- Projects
- Olena
- Date
- 2015-05-14
Abstract
Latecki et al. have introduced the notion of well-composed images, i.e., a class of images free from the connectivities paradox of discrete topology. Unfortunately natural and synthetic images are not a priori well-composed, usually leading to topological issues. Making any $n$D image well-composed is interesting becauseafterwards, the classical connectivities of components are equivalent, the component boundaries satisfy the Jordan separation theorem, and so on. In this paper, we propose an algorithm able to make $n$D images well-composed without any interpolation. We illustrate on text detection the benefits of having strong topological properties.
Bibtex (lrde.bib)
@InProceedings{ boutry.15.icip, author = {Nicolas Boutry and Thierry G\'eraud and Laurent Najman}, title = {How to Make {$n$D} Images Well-Composed Without Interpolation}, booktitle = {Proceedings of the IEEE International Conference on Image Processing (ICIP)}, year = {2015}, month = sep, address = {Qu\'ebec City, Canada}, abstract = {Latecki et al. have introduced the notion of well-composed images, i.e., a class of images free from the connectivities paradox of discrete topology. Unfortunately natural and synthetic images are not a priori well-composed, usually leading to topological issues. Making any $n$D image well-composed is interesting because, afterwards, the classical connectivities of components are equivalent, the component boundaries satisfy the Jordan separation theorem, and so on. In this paper, we propose an algorithm able to make $n$D images well-composed without any interpolation. We illustrate on text detection the benefits of having strong topological properties.} }