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Issue:Intuitionistic fuzzy sets and their use in image classification

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Title of paper: Intuitionistic fuzzy sets and their use in image classification
Author(s):
Alžbeta Michalíková
Faculty of Natural Sciences, Matej Bel University, Tajovského 40, 974 01, Banská Bystrica, Slovakia
Mathematical Institute, Slovak Academy of Sciences, Ďumbierska 1, Banská Bystrica, Slovakia
alzbeta.michalikova@umb.sk
Published in: Notes on Intuitionistic Fuzzy Sets, Volume 25 (2019), Number 2, pages 60–66
DOI: https://doi.org/10.7546/nifs.2019.25.2.60-66
Download:  PDF (769  Kb, Info)
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 which are characterized by some patterns. The theory of intuitionistic fuzzy sets is used for classification of the images. In the first step is showed the way how this type of images could be represented as the vectors. Then the membership and non-membership value to each coordinate are calculated and finally the value of similarity measure between patterns and specific image is computed. Classification is performed with respect to the valued of similarity measure.
Keywords: Intuitionistic fuzzy sets, Similarity measure, Image classification.
AMS Classification: 03C98, 03E72.
References:
  1. Atanassov, K. T. (1983). Intuitionistic Fuzzy Sets, VII ITKR Session, Sofia, 20-23 June 1983 (Deposed in Centr. Sci.-Techn. Library of the Bulg. Acad. of Sci., 1697/84) (in Bulgarian). Reprinted: Int. J. Bioautomation, 2016, 20(S1), S1–S6.
  2. Intarapaiboon, P. (2016). Text classification using similarity measures on intuitionistic fuzzy sets. SCIENCEASIA, 42 (1), 52–60.
  3. Michalíková, A. & Vagač, M. (2016). A tire tread pattern detection based on fuzzy logic. Flexible Query Answering Systems 2015. Springer, Cham, 381–388.
  4. Vagač, M., Melicherčík, M., Marko, M., Trhan, P., Michalíková, A., Kliment R. & Drapka, R. (2015). Crawling images with web browser support. 13th International IEEE Scientific Conference on Informatics'2015, 286–289.
  5. Vagač, M., Melicherčík, M. & Schon, J. (2015). Classification of tire images in order to obtain the best possible tire tread sample. The 5th International Scientific Conference, Applied Natural Science 2015. September 30-October 2, 2015, Jasn; Trnava : UCM, 173.
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