Fuzzy Rule-Based Classifier for Content-Based Image Retrieval

Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 183)

Abstract

At present a great deal of research is being done in different aspects of Content-Based Image Retrieval System (CBIR). Thus, it is necessary to develop appropriate information systems to efficiently manage datasets. Image classification is one of the most important services in image retrieval that must support these systems. The primary issue we have addressed is: how can the fuzzy set theory be used to handle crisp data for images. We propose how to introduce fuzzy rule-based classification for image objects. To achieve this goal we have constructed fuzzy rule-based classifiers, taking into account crisp data. In this chapter we present the results of the use of this fuzzy rule-based system in our CBIR.

Keywords

Fuzzy Rule Zernike Moment Graphical Object CBIR System Minor Axis Length 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  1. 1.Systems Research InstitutePolish Academy of SciencesWarsawPoland

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