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Point Cloud Processing with the Combination of Fuzzy Information Measure and Wavelets

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Soft Computing Applications (SOFA 2016)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 633))

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Abstract

Processing of remotely sensed point clouds is a crucial issue for many applications, including robots operating autonomously in real world environments, etc. The pre-processing is almost an important step which includes operations such as remove of systematic errors, filtering, feature detection and extraction. In this paper we introduce a new preprocessing strategy with the combination of fuzzy information measure and wavelets that allows precise feature extraction, denoising and additionally effective compression of the point cloud. The suitable setting of the applied wavelet and parameters have a great impact on the result and depends on the aim of preprocessing that usually is a challenge for the users. In order to address this problem the fuzzy information measure has been proposed that supports the adaptive setting of the parameters. Additionally a fuzzy performance measure has been introduced, that can reduce the complexity of the procedure. Simulation results validate the efficiency and applicability of this method.

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Acknowledgements

This work has been sponsored by the Hungarian National Scientific Research Fund (OTKA 105846). This publication is also the partial result of the Research & Development Operational Programme for the project “Modernisation and Improvement of Technical Infrastructure for Research and Development of J. Selye University in the Fields of Nanotechnology and Intelligent Space”, ITMS 26210120042, co-funded by the European Regional Development Fund.

Author information

Authors and Affiliations

  1. Doctoral School of Applied Informatics and Applied Mathematics, Óbuda University, Bécsi út 96/b, Budapest, 1034, Hungary

    Adrienn Dineva

  2. Doctoral School of Computer Science, Department of Information Technologies, Universitá degli Studi di Milano, Crema Campus, 65 Via Bramante, 26013, Crema (CR), Italy

    Adrienn Dineva

  3. Department of Mathematics and Informatics, J. Selye University, Komarno, Slovakia

    Annamária R. Várkonyi-Kóczy

  4. Department of Information Technologies, Universitá degli Studi di Milano, Crema, Italy

    Vincenzo Piuri

  5. Antal Bejczy Center for Intelligent Robotics (ABC iRob), Óbuda University, Budapest, Hungary

    József K. Tar

Authors
  1. Adrienn Dineva
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  2. Annamária R. Várkonyi-Kóczy
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  3. Vincenzo Piuri
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  4. József K. Tar
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Corresponding author

Correspondence to Adrienn Dineva .

Editor information

Editors and Affiliations

  1. Department of Automatics and Applied Informatics, Faculty of Engineering, Aurel Vlaicu University of Arad, Arad, Romania

    Valentina Emilia Balas

  2. University of Canberra, Canberra, Aust Capital Terr, Australia

    Lakhmi C. Jain

  3. Department of Automatics and Applied Informatics, Faculty of Engineering, Aurel Vlaicu University of Arad, Arad, Romania

    Marius Mircea Balas

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Dineva, A., Várkonyi-Kóczy, A.R., Piuri, V., Tar, J.K. (2018). Point Cloud Processing with the Combination of Fuzzy Information Measure and Wavelets. In: Balas, V., Jain, L., Balas, M. (eds) Soft Computing Applications. SOFA 2016. Advances in Intelligent Systems and Computing, vol 633. Springer, Cham. https://doi.org/10.1007/978-3-319-62521-8_39

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  • DOI: https://doi.org/10.1007/978-3-319-62521-8_39

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-62520-1

  • Online ISBN: 978-3-319-62521-8

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