On the Generalization of the Fuzzy Morphological Operators for Edge Detection

DOI

10.2991/ifsa-eusflat-15.2015.153How to use a DOI?

Keywords

Fuzzy mathematical morphology, edge detection, t-norms, fuzzy implications, hysteresis.

Abstract

The morphological gradient is a widely used edge detector for grey-level images in many applications. In this paper, we generalize the definition of the morphological gradient of the fuzzy mathematical morphology based on t-norms. Concretely, instead of defining the morphological gradient from the usual definitions of fuzzy dilation and erosion, where the minimum and the maximum are used, we define it from generalized fuzzy dilation and erosion, where we consider a general t-norm and t-conorm, respectively. Once the generalized morphological gradient is defined, we determine which t-norm and tconorm have to be considered in order to obtain a high performance edge detector. Some t-norms and their dual t-conorms are taken into account and the experimental results conclude that the t-norms of the Schweizer-Sklar family generate a morphological gradient which outperforms notably the classical morphological gradient.

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  - Manuel González-Hidalgo
AU  - Sebastia Massanet
AU  - Arnau Mir
AU  - Daniel Ruiz-Aguilera
PY  - 2015/06
DA  - 2015/06
TI  - On the Generalization of the Fuzzy Morphological Operators for Edge Detection
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  - 1082
EP  - 1089
SN  - 1951-6851
UR  - https://doi.org/10.2991/ifsa-eusflat-15.2015.153
DO  - 10.2991/ifsa-eusflat-15.2015.153
ID  - González-Hidalgo2015/06
ER  -