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A Compound Moving Average Bidirectional Texture Function Model

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Multimedia and Network Information Systems

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 506))

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Abstract

This paper describes a simple novel compound random field model capable of realistic modelling the most advanced recent representation of visual properties of surface materials—the bidirectional texture function. The presented compound random field model combines a non-parametric control random field with local multispectral models for single regions and thus allows to avoid demanding iterative methods for both parameters estimation and the compound random field synthesis. The local texture regions (not necessarily continuous) are represented by an analytical bidirectional texture function model which consists of single scale factors modeled by the three-dimensional moving average random field model which can be analytically estimated as well as synthesized.

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Acknowledgments

This research was supported by the Czech Science Foundation project GAČR 14-10911S.

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Authors and Affiliations

  1. Institute of Information Theory and Automation of the CAS, Prague, Czech Republic

    Michal Haindl & Michal Havlíček

Authors
  1. Michal Haindl
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  2. Michal Havlíček
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Corresponding author

Correspondence to Michal Haindl .

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Editors and Affiliations

  1. Department of Information Systems, Faculty of Computer Science and Management, Wrocław University of Science and Technology, Wroclaw, Poland

    Aleksander Zgrzywa

  2. Department of Information Systems, Faculty of Computer Science and Management, Wrocław University of Science and Technology, Wrocław, Poland

    Kazimierz Choroś

  3. Department of Information Systems, Faculty of Computer Science and Management, Wrocław University of Science and Technology, Wrocław, Poland

    Andrzej Siemiński

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Haindl, M., Havlíček, M. (2017). A Compound Moving Average Bidirectional Texture Function Model. In: Zgrzywa, A., Choroś, K., Siemiński, A. (eds) Multimedia and Network Information Systems. Advances in Intelligent Systems and Computing, vol 506. Springer, Cham. https://doi.org/10.1007/978-3-319-43982-2_8

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  • DOI: https://doi.org/10.1007/978-3-319-43982-2_8

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-43981-5

  • Online ISBN: 978-3-319-43982-2

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