Open AccessPERFORMANCE ANALYSIS OF FUZZY MATHEMATICAL MORPHOLOGY OPERATORS ON NOISY MRI
Author(s) -
Agustina Bouchet,
Freddy Benalcazar Palacios,
Marcel Brun,
Virginia L. Ballarin
Publication year - 2014
Publication title -
latin american applied research
Language(s) - English
Resource type - Journals
eISSN - 1851-8796
pISSN - 0327-0793
DOI - 10.52292/j.laar.2014.446
Subject(s) - robustness (evolution) , fuzzy logic , mathematical morphology , computer science , artificial intelligence , noise (video) , pattern recognition (psychology) , image processing , image (mathematics) , biochemistry , gene , chemistry
Despite a large amount of publications on Fuzzy Mathematical Morphology, little effort was done on systematic evaluation of the performance of this technique. The goal of this work is to compare the robustness against noise of Fuzzy and non Fuzzy Morphological operators when applied to noisy images. Magnetic Resonance Images (MRI) of the brain are a kind of images containing some characteristics that make fuzzy operators an interesting choice, because of their intrinsic noise and imprecision. The robustness was evaluated as the degree in which the results of the operators are not affected by artificial noise in the images. In the analysis we compared different implementation of Fuzzy Mathematical Morphology, and observed that in most of the cases they show higher robustness against noise than the classical morphological operators.