A logical representation of images by means of multi-rough sets for Kansei image retrieval

Authors:
Tetsuya Murai;Sadaaki Miyamoto;Yasuo Kudo
Affiliations:
Division of Computer Science, Graduate School of Information Science and Technology, Hokkaido University, Sapporo, Japan;Department of Risk Engineering, Faculty of Systems and Information Engineering, University of Tsukuba, Ibaraki, Japan;Department of Computer Science and Systems Engineering, Muroran Institute of Technology, Muroran, Japan
Venue:
RSKT'07 Proceedings of the 2nd international conference on Rough sets and knowledge technology
Year:
2007

Citing 4
Cited 0

Principles of database and knowledge-base systems, Vol. I

Principles of database and knowledge-base systems, Vol. I
Variable precision rough set model

Journal of Computer and System Sciences
Rough Sets: Theoretical Aspects of Reasoning about Data

Rough Sets: Theoretical Aspects of Reasoning about Data
Generalizations of multisets and rough approximations

International Journal of Intelligent Systems - Granular Computing and Data Mining

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this paper, we examine a logical representation of images by means of multi-rough sets. We introduce a level of granularization into a color space and then define approximations of images. Further we extend the idea to conditionals in images, which is expected to give a basis of image indexing and retrieval by images themselves.