ISSN 0021-3454 (print version)
ISSN 2500-0381 (online version)
Menu

9
Issue
vol 63 / September, 2020
Article

DOI 10.17586/0021-3454-2019-62-11-1005-1014

UDC 535.6

ANALYSIS OF THE CONVERSION ACCURACY OF THE COLOR SATURATION IN MODERN SOFTWARE

M. V. Belodedov
N. E. Bauman Moscow State Tech-nical Universitу;


N. M. Zotov
Volgograd State Technical University;


A. V. Khoperskov
Volgograd State University, Department of Information Systems and Computer Simulation;


A. M. Chmutin
Volgograd State University, Department of Information Systems and Computer Simulation; Associate Professor


V. A. Chuiko
ITMO University; senior lecturer


Abstract. Color saturation control tools of modern computer graphics software is analyzed. For the case of a virtual instrumentation, the concomitant error is defined as a three-dimensional value, and a classification of the error components is proposed. Two new shift-type components are introduced, and their properties are studied using sampling from 24 software packages. The criticality of one of the error components, threatening the integrity of visual information in the process of contrast transformation, is revealed. It is shown that the existing tools are not able to provide systemic color saturation contrast control, and this lim-its their application area to the tasks of image synthesis only.
Keywords: software metrology, transformation of color saturation, contrast of saturations, contrast transformation errors, graphic information integrity, expert applications

References:
  1. Grebenyuk P.E., Chmutin A.M., Chuyko V.A. Journal of Instrument Engineering, 2018, no. 1(61), pp. 71–77. DOI: 10.17586/0021-3454-2018-61-1-71-77. (in Russ.)
  2. Shapiro L.G., Stockman G.C. Computer Vision, Upper Saddle River, Prentice Hall, 2001, 580 p.
  3. Forsyth D.A., Ponce J. Computer Vision: A Modern Approach, Upper Saddle River, Prentice Hall, 2012, 761 p.
  4. Selivanov M.N., Fridman A.E., Kudryashova Zh.F. Kachestvo izmereniy: Metrologicheskaya spravochnaya kniga (Measurement Quality: Metrological Reference Book), Leningrad, 1987, 295 р. (in Russ.)
  5. Chmutin A.M. Intern. Journal of Open Information Technologies, 2019, no. 1(7), pp. 12–24, http://www.injoit.org/ index.php/j1/article/view/632/645/632-2038-1-РВ.pdf. (in Russ.)
  6. Helmholtz H. Treatise on Physiological Optics, vol. 2. The Sensations of Vision, Rochester, JOSA, 1924, 480 p.
  7. Smirnov S.A. Preobrazovaniye opticheskikh signalov (Optical Signal Conversion), St. Petersburg, 2008, 113 р. (in Russ.)
  8. http://www.web.snauka.ru/issues/2018/03/85975. (in Russ.)
  9. Gaudin J. Colorimétrie appliquée à la vidéo, Paris, Dunod, 2012, 320 p.
  10. Alekhin A.A., Gorbunova E.V., Chertov A.N., Shitov D.D. Journal of Instrument Engineering, 2012, no. 12(55), pp. 65–66. (in Russ.)
  11. Poynton C. Digital Video and HDTV Algorithms and Interfaces, San Francisco, Elsevier Science, 2003, 692 p.
  12. Andronova N.E., Grebenyuk P.E., Chmutin A.M. Lazerno-informatsionnyye tekhnologii v meditsine, biologii, geoekologii i transporte (Laser Information Technologies in Medicine, Biology, Geoecology and Transport), Proceedings of the 22nd International Conference, Novorossiysk, 2014, рр. 58–59. (in Russ.)
  13. Tropchenko A.Yu., Tropchenko A.A. Tsifrovaya obrabotka signalov. Metody predvaritel'noy obrabotki (Digital Signal Processing. Preprocessing Methods), St. Petersburg, 2009, 100 р. (in Russ.)
  14. Soifer V.A., ed., Metody komp'yuternoy obrabotki izobrazheniy (Methods of Computer Image Processing), Moscow, 2003, 784 р. (in Russ.)