Gradient extraction operators for discrete interval-valued data

DOI

10.2991/ifsa-eusflat-15.2015.118How to use a DOI?

Keywords

Image processing, interval-valued information, edge detection, canny method.

Abstract

Digital images are generally created as discrete measurements of light, as performed by dedicated sensors. Consequently, each pixel contains a discrete approximation of the light inciding in a sensor element. The nature of this measurement implies certain uncertainty due to discretization matters. In this work we propose to model such uncertainty using intervals, further leading to the generation of so-called interval-valued images. Then, we study the partial differentiation of such images, putting a spotlight on antisymmetric convolution operators for such task. Finally, we illustrate the utility of the interval-valued images by studying the behaviour of an extended version of the well-known Canny edges detection method.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Carlos Lopez-Molina
AU  - Cedric Marco-Detchart
AU  - Juan Cerron
AU  - Humberto Bustince
AU  - Bernard De Baets
PY  - 2015/06
DA  - 2015/06
TI  - Gradient extraction operators for discrete interval-valued data
BT  - Proceedings of the 2015 Conference of the International Fuzzy Systems Association and the European Society for Fuzzy Logic and Technology
PB  - Atlantis Press
SP  - 836
EP  - 843
SN  - 1951-6851
UR  - https://doi.org/10.2991/ifsa-eusflat-15.2015.118
DO  - 10.2991/ifsa-eusflat-15.2015.118
ID  - Lopez-Molina2015/06
ER  -