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A Perceptual Subjectivity Notion in Interactive Content-Based Image Retrieval Systems

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Intelligent Multimedia Processing with Soft Computing

Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 168))

Abstract

This chapter presents a new framework called fuzzy relevance feedback in interactive content-based image retrieval (CBIR) systems. Conventional binary labeling scheme in relevance feedback requires a hard-decision to be made on the relevance of each retrieved image. This is inflexible as user interpretation 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 priority. It is, therefore, inadequate to describe the users’ fuzzy perception of image similarity with crisp logic. In view of this, a fuzzy framework is introduced to integrate the users’ imprecise interpretation of visual contents into relevance feedback. An efficient learning approach is developed using a fuzzy radial basis function network (FRBFN). The network is constructed based on hierarchical clustering algorithm. The underlying network parameters are optimized by adopting a gradient-descent-based training strategy due to its computational efficiency. Experimental results using a database of 10,000 images demonstrate the effectiveness of the proposed method.

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Authors and Affiliations

  1. School of Electrical and Electronic Engineering, Nanyang Technological University, Nanyang Avenue, Singapore, 639798

    Kui Wu & Kim-Hui Yap

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  1. Kui Wu
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  2. Kim-Hui Yap
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Editor information

Editors and Affiliations

  1. School of Electrical and Electronic Engineering, Nanyang Technological University, Nanyang Avenue, Singapore, 639798

    Yap-Peng Tan , Kim Hui Yap  & Lipo Wang ,  & 

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© 2005 Springer-Verlag Berlin Heidelberg

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Wu, K., Yap, KH. (2005). A Perceptual Subjectivity Notion in Interactive Content-Based Image Retrieval Systems. In: Tan, YP., Yap, K.H., Wang, L. (eds) Intelligent Multimedia Processing with Soft Computing. Studies in Fuzziness and Soft Computing, vol 168. Springer, Berlin, Heidelberg . https://doi.org/10.1007/3-540-32367-8_3

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  • DOI: https://doi.org/10.1007/3-540-32367-8_3

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-23053-3

  • Online ISBN: 978-3-540-32367-9

  • eBook Packages: EngineeringEngineering (R0)

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