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A Gaussian-Fuzzy Content Feature Recognition System for Digital Media Asset Objects

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Digital Libraries: International Collaboration and Cross-Fertilization (ICADL 2004)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 3334))

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Abstract

One of the key issues within the research of Media Assets is the description and intelligent recognition of content-based features. Upon the basis of massive fundamental research, we present in this paper a configurable content description and recognition model based on a Gaussian-Fuzzy membership system. Multiple and partial memberships and compatibility for various algorithms are supported in this architecture.

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Author information

Authors and Affiliations

  1. School of Computer Science and Software, Communication University of China, No.1 Dingfuzhuang Dongjie, Beijing, 100024, P.R. China

    Sanxing Cao & Rui Lu

Authors
  1. Sanxing Cao
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  2. Rui Lu
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Editor information

Editors and Affiliations

  1. Shanghai Jiao Tong University, Shanghai, P.R. China

    Zhaoneng Chen

  2. Department of Management Information Systems, Eller College of Management, The University of Arizona, 85721, AZ, USA

    Hsinchun Chen

  3. Shanghai Library, Shanghai, P.R. China

    Qihao Miao

  4. BASICS, Department of Computer Science and Engineering, Shanghai Jiao Tong University, 200030, Shanghai, China

    Yuxi Fu

  5. Digital Library Research Laboratory, Virginia Tech, USA

    Edward Fox

  6. School of Computer Engineering, Nanyang Technological University,  

    Ee-peng Lim

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© 2004 Springer-Verlag Berlin Heidelberg

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Cao, S., Lu, R. (2004). A Gaussian-Fuzzy Content Feature Recognition System for Digital Media Asset Objects. In: Chen, Z., Chen, H., Miao, Q., Fu, Y., Fox, E., Lim, Ep. (eds) Digital Libraries: International Collaboration and Cross-Fertilization. ICADL 2004. Lecture Notes in Computer Science, vol 3334. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30544-6_48

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  • DOI: https://doi.org/10.1007/978-3-540-30544-6_48

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-24030-3

  • Online ISBN: 978-3-540-30544-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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