Authors:
Hema Nair
1
and
Ian Chai
2
Affiliations:
1
Faculty of Engineering and Technology, Multimedia University, Malaysia
;
2
Faculty of Engineering, Multimedia University, Malaysia
Keyword(s):
Linguistic summary, data mining, fuzzy logic, genetic algorithm, remote-sensed image.
Related
Ontology
Subjects/Areas/Topics:
Advanced Applications of Fuzzy Logic
;
Artificial Intelligence
;
Artificial Intelligence and Decision Support Systems
;
Biomedical Engineering
;
Business Analytics
;
Data Engineering
;
Data Mining
;
Databases and Information Systems Integration
;
Datamining
;
Enterprise Information Systems
;
Health Information Systems
;
Sensor Networks
;
Signal Processing
;
Soft Computing
Abstract:
The objective of this paper is to propose an approach to describe patterns in remote-sensed images utilising fuzzy logic. The general form of a linguistically quantified proposition is “QY’s are F” where Q is a fuzzy linguistic quantifier, Y is a class of objects and F is a summary that applies to that class. The truth of such a proposition can be determined for each object characterised by a tuple in the database. Fuzzy descriptions of linguistic summaries help to evaluate the degree to which a summary describes an object or pattern in the image. A genetic algorithm technique is used to obtain optimal solutions that describe all the objects or patterns in the database. Image mining is used to extract unusual patterns from multi-dated satellite images of a geographic area.