Chapter 2. Morphological Image Analysis for Computer Vision Applicationsстатья

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Дата последнего поиска статьи во внешних источниках: 20 апреля 2016 г.

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[1] Chapter 2. morphological image analysis for computer vision applications / Y. V. Vizilter, Y. P. Pyt’ev, A. I. Chulichkov, L. M. Mestetskiy // Computer Vision in Control Systems-1 Mathematical Theory, Favorskaya, Margarita N., Jain, Lakhmi C. (Eds.). — Springer International Publishing Switzerland, 2015. — P. 9–54. Глава 2 в монографии. Стр.9-54 Chapter 2. Morphological Image Analysis for Computer Vision Applications. Y.V. Vizilter, Y.P. Pyt’ev, A.I. Chulichkov and L.M. Mestetskiy 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. [ DOI ]

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