Analysis of fuzzy morphology in spore counts of mycorrhizal fungi

Mathematical Morphology presents a systematic model to extract geometric features of images using morphological operators that transform the original image into another, using a third image called structuring element. Fuzzy mathematical morphology extends morphological operators for images in grayscale and colored ones, using the theory of fuzzy sets, especially fuzzy logics, where operators are defined using the notions of R-implications and T-norms. In this work, an automatic method was proposed for counting mycorrhizal fungi spores. Spores counting is done manually using a ribbed plate and a stereomicroscope. This paper proposes an automatic method for counting spores by using Gödel morphology. It provides a comparison with a method using neural network.