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RoughCut–New Approach to Segment High-Resolution Images

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Artificial Intelligence and Soft Computing (ICAISC 2016)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9693))

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Abstract

We introduce a texture-based modification of the GrabCut algorithm that significantly improves its performance for high-resolution images but with a slight decrease in accuracy. This consists of five steps: expansion, convolution, shrinkage, GrabCut of the shrunk image, and enlargement. The results showed that modified algorithm is three times faster than the original one. At the same time, there is no significant difference between the average F1-measures obtained for both algorithms in case of high-resolution images. Therefore, it can be successfully used in semi-automatic segmentation of such images.

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Authors and Affiliations

  1. Faculty of Mathematics and Computer Science, The Institute of Computer Science and Computer Mathematics, Jagiellonian University, ul. Łojasiewicza 6, 30-348, Kraków, Poland

    Mateusz Babiuch, Bartosz Zieliński & Marek Skomorowski

Authors
  1. Mateusz Babiuch
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  2. Bartosz Zieliński
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  3. Marek Skomorowski
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Corresponding author

Correspondence to Bartosz Zieliński .

Editor information

Editors and Affiliations

  1. Częstochowa University of Technology, Czestochowa, Poland

    Leszek Rutkowski

  2. Częstochowa University of Technology, Czestochowa, Poland

    Marcin Korytkowski

  3. Częstochowa University of Technology, Czestochowa, Poland

    Rafał Scherer

  4. AGH University of Science and Technology, Krakow, Poland

    Ryszard Tadeusiewicz

  5. University of California, Berkeley, California, USA

    Lotfi A. Zadeh

  6. University of Louisville, Louisville, Kentucky, USA

    Jacek M. Zurada

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Babiuch, M., Zieliński, B., Skomorowski, M. (2016). RoughCut–New Approach to Segment High-Resolution Images. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L., Zurada, J. (eds) Artificial Intelligence and Soft Computing. ICAISC 2016. Lecture Notes in Computer Science(), vol 9693. Springer, Cham. https://doi.org/10.1007/978-3-319-39384-1_52

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  • DOI: https://doi.org/10.1007/978-3-319-39384-1_52

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-39383-4

  • Online ISBN: 978-3-319-39384-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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