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The study of images of dynamically changing scenes in the colorimetric space
Ipatov Yurii Arkad'evich

PhD in Technical Science

Associate Professor of the Department of Informatics at the Volga State University of Technology

424000, Russia, Mari El, Yoshkar-Ola, pl. Lenina, d. 3

philsilver@mail.ru
Totskii Aleksei Andreevich

student, Volga State University of Technology

424000, Russia, Marii El, g. Ioshka-Ola, ul. Lenina, 3, aud. 525

alex.totsky@yandex.ru
Abstract. The object of research is the image of a dynamically changing scene of artificial origin on the complex and statistically inhomogeneous background. The subject of research is the transformation methods and standard approaches of representation of color digital images in three dimensions. The study focuses on almost all basic colorimetric spaces used in building a clusters of object / background. Formation of the samples is carried out by the method of supervised learning. Calculation of objective indicators and comparison of subjective characteristics allows to determine the optimal color space for subsequent synthesis of algorithm for effective segmentation of this class of images. When solving the task authors used image processing techniques, probability theory, mathematical logic, mathematical statistics, the unit of mathematical analysis, linear algebra, mathematical modeling methods, theory of algorithms and methods of object-oriented programming. The novelty of the study is in determination of the optimal color space separation of clusters object / background for images of a given class. Visual characteristics of considered methods of representation of colorimetric spaces confirmed objective indicators of calculus. The main conclusions of the study is that RGB color space is the best choice for color segmentation algorithm synthesized as the representation of objects and the background form a weakly overlapping clusters.
Keywords: dynamically changing scene, color space, color images, clustering, colorimetric model, convex hull, device-dependent color models, spot description of the scene, point description methods, recognition by points
DOI: 10.7256/2306-4196.2015.4.16158
Article was received: 17-08-2015

Review date: 18-08-2015

Publish date: 25-09-2015

This article written in Russian. You can find full text of article in Russian here.

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