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Edge Curve Estimation by the Nonparametric Parzen Kernel Method

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Neural Information Processing (ICONIP 2020)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1332))

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Abstract

The article concerns the problem of finding the spatial curve which is the line of the abrupt or jump change in the 3d-shape, namely: the edge curve. There are many real applications where such a problems play a significant role. For instance, in computer vision in detection of edges in monochromatic pictures used in e.g. medicine diagnostics, biology and physics; in geology in analysis of satellite photographs of the earth surface for maps and/or determination of borders of forest areas, water resources, rivers, rock cliffs etc. In architecture the curves arising as a result of intersecting surfaces often are also objects of interest. The main focus of this paper is detection of abrupt changes in patterns defined by multidimensional functions. Our approach is based on the nonparametric Parzen kernel estimation of functions and their derivatives. An appropriate use of nonparametric methodology allows to establish the shape of an interesting edge curve.

Part of this research was carried out by the second author during his visit of the Westpomeranian University of Technology while on sabbatical leave from Concordia University.

Research of the first author financed under the program of the Polish Minister of Science and Higher Education under the name “Regional Initiative of Excellence” in the years 2019–2022 project number 020/RID/2018/19, the amount of financing 12,000,000.00 PLN. Research of the second author supported by the Natural Sciences and Engineering Research Council of Canada under Grant RGPIN-2015-06412.

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Author information

Authors and Affiliations

  1. Institute of Computational Intelligence, Czȩstochowa University of Technology, Czȩstochowa, al. Armii Krajowej 36, 42-200, Czȩstochowa, Poland

    Tomasz Gałkowski

  2. Department of Computer Science and Software Engineering, Concordia University, Montreal, QC, H3G 1M8, Canada

    Adam Krzyżak

  3. Department of Electrical Engineering, Westpomeranian University of Technology, 70-310, Szczecin, Poland

    Tomasz Gałkowski & Adam Krzyżak

Authors
  1. Tomasz Gałkowski
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  2. Adam Krzyżak
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Corresponding author

Correspondence to Tomasz Gałkowski .

Editor information

Editors and Affiliations

  1. Department of AI, Ping An Life, Shenzhen, China

    Haiqin Yang

  2. Faculty of Information Technology, King Mongkut's Institute of Technology Ladkrabang, Bangkok, Thailand

    Kitsuchart Pasupa

  3. City University of Hong Kong, Kowloon, Hong Kong

    Andrew Chi-Sing Leung

  4. Department of Computer Science and Engineering, Hong Kong University of Science and Technology, Hong Kong, Hong Kong

    James T. Kwok

  5. School of Information Technology, King Mongkut's University of Technology Thonburi, Bangkok, Thailand

    Jonathan H. Chan

  6. The Chinese University of Hong Kong, New Territories, Hong Kong

    Irwin King

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Gałkowski, T., Krzyżak, A. (2020). Edge Curve Estimation by the Nonparametric Parzen Kernel Method. In: Yang, H., Pasupa, K., Leung, A.CS., Kwok, J.T., Chan, J.H., King, I. (eds) Neural Information Processing. ICONIP 2020. Communications in Computer and Information Science, vol 1332. Springer, Cham. https://doi.org/10.1007/978-3-030-63820-7_43

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  • DOI: https://doi.org/10.1007/978-3-030-63820-7_43

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-63819-1

  • Online ISBN: 978-3-030-63820-7

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