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Morphological Image Analysis for Computer Vision Applications

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Computer Vision in Control Systems-1

Part of the book series: Intelligent Systems Reference Library ((ISRL,volume 73))

Abstract

Some original and novel morphological concepts and tools are presented in this chapter as well as required amount of mathematical morphological basics. The continuous binary morphology based on a computational geometry is presented as a very fast approach to shape representation via real-time computation of figures’ skeletons. A skeletal representation of the figure is formed as a skeleton graph, and the radial function is determined in skeleton points. The proposed morphological spectrum is the multi-scale morphological shape description and analysis tools based on granulometry. It is shown how the tasks of change detection and shape matching in images can be solved using a morphological image analysis. The projective morphology as a generalized framework based on the mathematical morphology and the morphological image analysis provides fast and efficient solutions of morphological segmentation problem in complex images.

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Acknowledgments

Authors thank all colleagues from Moscow Morphological Workshop in the Lomonosov Moscow state university (supervised by Prof. Y. Pyt’ev) for many-years fruitful and kind discussions. Special thanks are to Russian Fund of Basic Researches supported the morphological researches by a series of grants.

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Authors and Affiliations

  1. State Research Institute of Aviation Systems, 7, Viktorenko str., Moscow, 125319, Russian Federation

    Y.V. Vizilter

  2. M.V. Lomonosov Moscow State University, 1, Leninskie Gory, Moscow, 119991, Russian Federation

    Y.P. Pyt’ev & A.I. Chulichkov

  3. Moscow International University, 17, Leningradsky av., Moscow, 125040, Russian Federation

    L. M. Mestetskiy

Authors
  1. Y.V. Vizilter
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  2. Y.P. Pyt’ev
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  3. A.I. Chulichkov
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  4. L. M. Mestetskiy
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Correspondence to Y.V. Vizilter .

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Editors and Affiliations

  1. Department of Informatics and Computer Techniques, Siberian State Aerospace University, Krasnoyarsk, Russia

    Margarita N. Favorskaya

  2. Faculty of Education, Science, Technology and Mathematics, University of Canberra, Canberra, Australia

    Lakhmi C. Jain

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Vizilter, Y., Pyt’ev, Y., Chulichkov, A., Mestetskiy, L.M. (2015). Morphological Image Analysis for Computer Vision Applications. In: Favorskaya, M., Jain, L. (eds) Computer Vision in Control Systems-1. Intelligent Systems Reference Library, vol 73. Springer, Cham. https://doi.org/10.1007/978-3-319-10653-3_2

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