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Vestnik Moskovskogo Universiteta. Seriya 1. Matematika. Mekhanika, 2018, Number 1, Pages 3–11
(Mi vmumm3)
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This article is cited in 2 scientific papers (total in 2 papers)
Mathematics
Geometrical coding of colored images
G. V. Nosovskii Lomonosov Moscow State University, Faculty of Mechanics and Mathematics
Abstract:
Formal analysis and computer recognition of 2D color images is an important branch of modern computer geometry. However, existing algorithms, although they are highly developed, are not quite satisfactory and seem to be much worse than (unknown) algorithms, which our brain uses to analyze eye information. Almost all existing algorithms omit colors and deal with grayscale transformations only. But in many cases color information is important. In this paper a fundamentally new method of coding and analyzing color digital images is proposed. The main point of this method is that a full-color digital image is represented without dropping colors by a special 2D surface in 3D space, after which it is analyzed by methods of differential geometry rather than traditional gradient-based or Hessian-based methods (like SIFT, GLOH, SURF, Canny operator, and many other algorithms).
Key words:
pattern recognition, geometrical coding, coding surface, contour analysis, edge detection, computer vision, image processing, image stitching.
Received: 03.04.2017
Citation:
G. V. Nosovskii, “Geometrical coding of colored images”, Vestnik Moskov. Univ. Ser. 1. Mat. Mekh., 2018, no. 1, 3–11; Moscow University Mathematics Bulletin, 73:1 (2018), 1–8
Linking options:
https://www.mathnet.ru/eng/vmumm3 https://www.mathnet.ru/eng/vmumm/y2018/i1/p3
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