Issue:Intuitionistic fuzzy negations and their use in image classification

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Title of paper: Intuitionistic fuzzy negations and their use in image classification
Alžbeta Michalíková
Faculty of Natural Sciences, Matej Bel University, Tajovskeho 40, Banska Bystrica, Slovakia
Mathematical Institute, Slovak Academy of Sciences, Dumbierska 1, Banska Bystrica, Slovakia
Published in: Notes on Intuitionistic Fuzzy Sets, Volume 26 (2020), Number 3, pages 22–32
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Abstract: In this paper, the problem of classification of images is discussed. Our specific problem is that we need to classify tire images into selected classes. The classes are characterized by some patterns. In the first step images are represented as the vectors. Then the membership and non-membership value to each coordinate of the vector is calculated and the theory of intuitionistic fuzzy sets is used. In [7] the classification of images was performed with respect to the valued of so called Sim function, which was defined as a ratio of distance between pattern data and image data and distance between pattern data and the complement of image data. The complement of image data was obtained by using specific intuitionistic fuzzy negation. In [2] a list of 53 intuitionistic fuzzy negations was presented. We have decided to use some of these negations to improve the results of classification.
Keywords: Intuitionistic fuzzy sets, Intuitionistic fuzzy negations, Similarity measure, Image classification.
AMS Classification: 03C98, 03E72.
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