Overlap Functions-Based Fuzzy Mathematical Morphological Operators and Their Applications in Image Edge Extraction

As special aggregation functions, overlap functions have been widely used in the soft computing field. In this work, with aid of two new groups fuzzy mathematical morphology (FMM) operators were proposed and applied to image processing, they obtained better results than existing algorithms. First, based on structuring elements, first group FMM (called OSFMM operators) was proposed, their properties systematically analyzed. With implementation C-means (FCM) algorithm, a edge extraction algorithm OS-FCM algorithm) proposed. Then, second ORFMM relations. Another OR-FCM by using FCM algorithm. Finally, through segmentation experiments multiple standard images, actual effects above-mentioned algorithms relevant compared. The acquired demonstrate that work can extract complete foreground objects basis introducing least noise.