Anzeige
Erschienen in:
2008 | OriginalPaper | Buchkapitel
Image Threshold Computation by Modelizing Knowledge/Unknowledge by Means of Atanassov’s Intuitionistic Fuzzy Sets
verfasst von : Humberto Bustince, Miguel Pagola, Pedro Melo-Pinto, Edurne Barrenechea, Pedro Couto
Erschienen in: Fuzzy Sets and Their Extensions: Representation, Aggregation and Models
Verlag: Springer Berlin Heidelberg
Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.
Wählen Sie Textabschnitte aus um mit Künstlicher Intelligenz passenden Patente zu finden. powered by
Markieren Sie Textabschnitte, um KI-gestützt weitere passende Inhalte zu finden. powered by
In this chapter, a new thresholding technique using Atanassov’s intuitionistic fuzzy sets (A-IFSs) and restricted dissimilarity functions is introduced. We interpret the intuitionistic fuzzy index of Atanassov as the degree of unknowledge/ignorance of an expert for determining whether a pixel of an image belongs to the background or the object of the image. Under these conditions we construct an algorithm on the basis of A-IFSs for detecting the threshold of an image. Then we present a method for selecting from a set of thresholds of an image the best one. This method is based on the concept of fuzzy similarity. Lastly, we prove that in most cases our algorithm for selecting the best threshold takes the threshold calculated with the algorithm constructed on the basis of A-IFSs.