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ABSTRACT
Fuzzy geometric measures have been found to reflect the spatial ambiguity of an image. Therefore, the study of similarity of fuzzy numbers is crucial in decision making. In this work, an intuitionistic fuzzy similarity measure (IFSM) has been proposed to calculate the degree of similarity of generalized fuzzy numbers (GFNs). The IFSM has been developed by integrating the concept of centre of gravity (COG) points and intuitionistic fuzzy difference of distance of points of fuzzy numbers. Properties that are relevant for a similarity measure have also been derived for the proposed IFSM. Further, a few pattern sets available in literature have been compared and it was observed that the IFSM provides a very intuitive quantification. Finally, the similarity measure has been applied for a fingerprint matching problem.
DISCLOSURE STATEMENT
No potential conflict of interest was reported by the authors.
Additional information
Notes on contributors
J. Dhivya
J Dhivya is an assistant professor of mathematics at Kumaraguru College of Technology, Coimbatore, Tamil Nadu, India. She is currently pursuing PhD degree in fuzzy sets and decision making at Anna University, Chennai, India. Her main research interests are: fuzzy sets and systems, decision making, similarity measure, pattern recognition and image processing.
B. Sridevi
B Sridevi is an associate professor of mathematics at PSG College of Technology, Coimbatore, Tamil Nadu, India. She received the PhD degree in fuzzy decision making at Bharathiar University, Coimbatore, India. Her main research interests are: fuzzy sets and systems, decision making, similarity measure, pattern recognition and image processing.
E-mail: [email protected]