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Title of Journal: Multimed Tools Appl

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Abbravation: Multimedia Tools and Applications

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Kluwer Academic Publishers-Plenum Publishers

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DOI

10.1002/jcp.1041280120

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1573-7721

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Contentbased image retrieval using fuzzy perceptu

Authors: Kui Wu KimHui Yap
Publish Date: 2006/11/30
Volume: 32, Issue: 3, Pages: 235-251
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Abstract

In this paper a new framework called fuzzy relevance feedback in interactive contentbased image retrieval CBIR systems is introduced Conventional binary labeling scheme in relevance feedback requires a crisp decision to be made on the relevance of the retrieved images However it is inflexible as user interpretation of visual content varies with respect to different information needs and perceptual subjectivity In addition users tend to learn from the retrieval results to further refine their information requests It is therefore inadequate to describe the user’s fuzzy perception of image similarity with crisp logic In view of this we propose a fuzzy relevance feedback approach which enables the user to make a fuzzy judgement It integrates the user’s fuzzy interpretation of visual content into the notion of relevance feedback An efficient learning approach is proposed using a fuzzy radial basis function FRBF network The network is constructed based on the user’s feedbacks The underlying network parameters are optimized by adopting a gradientdescent training strategy due to its computational efficiency Experimental results using a database of 10000 images demonstrate the effectiveness of the proposed method

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