Novel similarity measures for Fermatean fuzzy sets and its applications in image processing

Abstract

Digital imaging is growing in our day-to-day life ranging from selfies to medical imaging. The extended applications of the field open doors for the researchers in the present-day context. The extraction of useful information from digital images is crucial because it depends on the various characteristics of the image. Fuzzy theory provides a better understanding of the image characteristics and, thus extracts meaningful information, even under uncertain situations. The present study reports the Fermatean fuzzy sets (FFSs) application in image processing while proposing similarity measures. These similarity measures highlight the perfect and precise results from an image while using multiple parameters of the image for information extraction. The study concludes that the proposed similarity measures provide a better estimation of data from an image used in image processing problems.