Classification using fuzzy geometric features

Author

Krivsha, Vitaly V. ; Butenkov, Sergey A.

Author_Institution

Taganrog State Univ. of Radio Eng., Russia

fYear

2002

fDate

2002

Firstpage

89

Lastpage

91

Abstract

The work describes a new approach to multidimensional data classification or clustering. "Radar" diagrams are the well-known and most widely used data visualization technique with an ability to be used in expert and man-machine systems. This paper extends our earlier work (Karkishchenko et al., 2000) in image analysis and classification by means of fuzzy geometric features for the fuzzy classification of arbitrary data, presented as a radar diagram. We develop a diagram shape matching methodology to accomplish the fuzzy geometric features technique for the man-machine expert systems.

Keywords

data visualisation; diagrams; expert systems; fuzzy set theory; pattern classification; pattern clustering; data clustering; data visualization; diagram shape matching methodology; expert systems; fuzzy classification; fuzzy geometric features; fuzzy set theory; image analysis; image classification; man-machine systems; multidimensional data classification; radar diagrams; Data analysis; Data engineering; Data visualization; Electrical capacitance tomography; Expert systems; Fuzzy set theory; Fuzzy sets; Identity-based encryption; Image processing; Shape;

fLanguage

English

Publisher

ieee

Conference_Titel

Artificial Intelligence Systems, 2002. (ICAIS 2002). 2002 IEEE International Conference on

Print_ISBN

0-7695-1733-1

Type

conf

DOI

10.1109/ICAIS.2002.1048060

Filename

1048060