Object hypothesis support in the context of knowledge-based fuzzy-possibilistic fusion of image descriptions

Author

Raptis, Sotiris N. ; Tzafestas, S.G.

Author_Institution

Dept. of Electr. & Comput. Eng., Nat. Tech. Univ. of Athens, Greece

Volume

1

fYear

2000

fDate

10-13 July 2000

Abstract

Single images are often not enough to reveal all of the information contained in them, either because of the measurement ambiguity or because of the observer´s imperfect knowledge. Integrating or fusing many knowledge sources is a recent trend in the pattern recognition field. In the work presented in this paper, fuzzy logic, which has been established to be a successful methodology in dealing with imprecision, provides a general conceptual framework and an analytical tool as well.

Keywords

fuzzy logic; image processing; knowledge based systems; possibility theory; sensor fusion; uncertainty handling; visual databases; vocabulary; analytical tool; conceptual framework; fuzzy feature modelling; fuzzy logic; image descriptions; image descriptors; imperfect observer knowledge; imprecision; knowledge source integration; knowledge-based fuzzy-possibilistic fusion; measurement ambiguity; object hypothesis support; pattern recognition; Cameras; Electric variables measurement; Image fusion; Image recognition; Image segmentation; Intelligent robots; Knowledge engineering; Laboratories; Pattern recognition; Robotics and automation;

fLanguage

English

Publisher

ieee

Conference_Titel

Information Fusion, 2000. FUSION 2000. Proceedings of the Third International Conference on

Conference_Location

Paris, France

Print_ISBN

2-7257-0000-0

Type

conf

DOI

10.1109/IFIC.2000.862458

Filename

862458