Call for Papers for the 27th International Conference on Intuitionistic Fuzzy Sets is now open!
Conference: 5–6 July 2024, Burgas, Bulgaria • EXTENDED DEADLINE for submissions: 15 APRIL 2024.
Conference: 5–6 July 2024, Burgas, Bulgaria • EXTENDED DEADLINE for submissions: 15 APRIL 2024.
Issue:Intuitionistic fuzzy negations and their use in image classification: Difference between revisions
Jump to navigation
Jump to search
(Created page with "{{PAGENAME}} {{PAGENAME}} Category:Publicati...") |
No edit summary |
||
(One intermediate revision by the same user not shown) | |||
Line 1: | Line 1: | ||
[[Category:Publications on intuitionistic fuzzy sets|{{PAGENAME}}]] | [[Category:Publications on intuitionistic fuzzy sets|{{PAGENAME}}]] | ||
[[Category:Publications in Notes on IFS|{{PAGENAME}}]] | [[Category:Publications in Notes on IFS|{{PAGENAME}}]] | ||
Line 21: | Line 20: | ||
| file = NIFS-26-3-22-32.pdf | | file = NIFS-26-3-22-32.pdf | ||
| format = PDF | | format = PDF | ||
| size = | | size = 533 | ||
| 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. | | 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. | | keywords = Intuitionistic fuzzy sets, Intuitionistic fuzzy negations, Similarity measure, Image classification. |
Latest revision as of 16:01, 30 October 2020
shortcut
|
|