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Differential Approximation of the 2-D Laplace Operator for Edge Detection in Digital Images

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Computational Collective Intelligence. Technologies and Applications (ICCCI 2010)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6423))

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Abstract

The paper presents the application of finite difference edge detection in digital images. For edge detection we use several methods. One of them is a method based on Laplace operator. This paper presents a differential approximation of the two-dimensional Laplace operator. The paper proposes a differential approximation, Laplace operator, based on 9-th lattice mask. Coefficients were determined using the Z transform. Optimization is based on the criterion of maximal compatibility differential approximation of Laplace filter with ideal. Mask parameters were chosen based on the analysis of the error function. Activity obtained filter has been tested on a digital image that contains many elements of geometry.

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References

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Author information

Authors and Affiliations

  1. Faculty of Electrical Engineering, West Pomeranian University of Technology, 26 Kwietnia 10, 71-126, Szczecin, Poland

    Jakub Pęksiński & Grzegorz Mikołajczak

Authors
  1. Jakub Pęksiński
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  2. Grzegorz Mikołajczak
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Editor information

Editors and Affiliations

  1. Department of Electronic Engineering, National Kaohsiung University of Applied Sciences, 415 Chien-Kung Road, 807, Kaohsiung, Taiwan

    Jeng-Shyang Pan

  2. Department of Computer Science and Information Engineering, National Taiwan University of Science and Technology, #43, Sec.4, Keelung Rd., 106, Taipei, Taiwan

    Shyi-Ming Chen

  3. Institute of Informatics, Wroclaw University of Technology, Str. Wyb. Wyspianskiego 27, 50-370, Wroclaw, Poland

    Ngoc Thanh Nguyen

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Pęksiński, J., Mikołajczak, G. (2010). Differential Approximation of the 2-D Laplace Operator for Edge Detection in Digital Images. In: Pan, JS., Chen, SM., Nguyen, N.T. (eds) Computational Collective Intelligence. Technologies and Applications. ICCCI 2010. Lecture Notes in Computer Science(), vol 6423. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16696-9_21

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  • DOI: https://doi.org/10.1007/978-3-642-16696-9_21

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-16695-2

  • Online ISBN: 978-3-642-16696-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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