摘要:Currently, Mathematical Morphology (MM) has becomea powerful tool in Digital Image Processing (DIP). Itallows processing images to enhance fuzzy areas,segment objects, detect edges and analyze structures.The techniques developed for binary images are a majorstepforwardintheapplicationofthistheorytograylevelimages. One of these techniques is based on fuzzy logicand on the theory of fuzzy sets.Fuzzy set s ha ve proved t o be strongl y advantageouswhen representing inaccuracies, not only regarding thespatial localization of objects in an image but also themembership of a certain pixel to a given class. Suchinaccuracies are inherent to real images either because ofthe presence of indefinite limits between the structures orobjects to be segmented within the image due to noisyacquisitions or directly because they are inherent to theimage formation methods.Our approach is to show how the fuzzy sets specificallyutilized in MM have turned into a functional tool in DIP