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Best-Fit Segmentation Created Using Flood-Based Iterative Thinning

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Image Processing and Communications Challenges 8 (IP&C 2016)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 525))

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Abstract

Classical methods of segmentation that use binarization in the preprocessing stage often do not provide the precise delineation of the range of objects. For example, this might be useful for images of the corneal endothelium obtained with specular or confocal microscopy. This article presents a solution that makes it possible to adjust the course of the segmentation in the valleys between cells. The algorithm is a combination of iterative thinning and a watershed algorithm that works by the gradual removal of points with increasingly lower brightness levels. The article also contains examples of output images and quality tests.

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Acknowledgement

This work was financed by the AGH - University of Science and Technology, Faculty of Geology, Geophysics and Environmental Protection as a part of statutory project.

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Authors and Affiliations

  1. Department of Geoinfomatics and Applied Computer Science, AGH University of Science and Technology, A. Mickiewicza 30 Av., 30–059, Krakow, Poland

    Adam Piórkowski

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  1. Adam Piórkowski
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Correspondence to Adam Piórkowski .

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Editors and Affiliations

  1. Institute of Telecommunications and Computer Sciences, UTP University of Science and Technology, Bydgoszcz, Poland

    Ryszard S. Choraś

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Piórkowski, A. (2017). Best-Fit Segmentation Created Using Flood-Based Iterative Thinning. In: Choraś, R. (eds) Image Processing and Communications Challenges 8. IP&C 2016. Advances in Intelligent Systems and Computing, vol 525. Springer, Cham. https://doi.org/10.1007/978-3-319-47274-4_7

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  • DOI: https://doi.org/10.1007/978-3-319-47274-4_7

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-47273-7

  • Online ISBN: 978-3-319-47274-4

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