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Computer Optics, 2020, Volume 44, Issue 4, Pages 606–617
DOI: https://doi.org/10.18287/2412-6179-CO-631
(Mi co827)
 

This article is cited in 4 scientific papers (total in 4 papers)

IMAGE PROCESSING, PATTERN RECOGNITION

About quantifying small color differences in digital images

I. G. Pal'chikovaa, E. S. Smirnova, O. A. Barinovab, I. V. Latyshovc, V. A. Vasilievb, A. V. Kondakovb

a Technological Design Institute of Scientific Instrument Engineering SB RAS, 41, Russkaya str., Novosibirsk, 630058, Russia
b The Volgograd Academy of the Russian Internal Affairs Ministry, 130,Istoricheskaya str., Volgograd, 400075, Russia
c The Saint Petersburg University of the Russian Internal Affairs Ministry, 1, Pilot Pilyutov str., Saint Petersburg, 198206, Russia
References:
Abstract: We discuss aspects of the use and possibilities provided by three-color colorimeters or digital cameras in problems of detecting small color differences by computer vision methods. The spectral dependence of the total color differences between pairs of visually indiscernible monochromatic stimuli is experimentally revealed. An experimental setup based on the UM-2 monochromator is created for producing a digital atlas of monochromatic stimuli at 1-nm increments. The atlas serves to test the color gamut and color differentiation of cameras. It is experimentally shown that in the visible spectral range a color difference of 3 units is detected by pairs of stimuli that are unevenly distributed across the spectrum and differ in wavelengths from 1 to 6 nm. The capabilities of computer vision are tested on the examples of identifying additional texts during a technical and forensic examination of documents.
A new algorithm is developed for finding and quantitatively characterizing color difference of inserts based on a digital image of the inscription. In the algorithm, the objective analysis of the image is divided into a block of color segmentation and that of color tone and color difference assessment. With such an approach, the color segmentation block performs preprocessing functions, making a border map for the classes with different colors for the subsequent calculations. The Otsu method of optimal global threshold transformation is for the first time applied to a problem of image segmentation by color saturation. The trial of the algorithm confirms its efficiency in the solution of expert tasks.
Keywords: digital camera color gamut, RGB sensor, color, monochromatic stimuli, dominant wavelength, saturation, digital image processing, Otsu algorithm, segmentation, color difference.
Received: 12.09.2019
Accepted: 01.06.2020
Document Type: Article
Language: Russian
Citation: I. G. Pal'chikova, E. S. Smirnov, O. A. Barinova, I. V. Latyshov, V. A. Vasiliev, A. V. Kondakov, “About quantifying small color differences in digital images”, Computer Optics, 44:4 (2020), 606–617
Citation in format AMSBIB
\Bibitem{PalSmiBar20}
\by I.~G.~Pal'chikova, E.~S.~Smirnov, O.~A.~Barinova, I.~V.~Latyshov, V.~A.~Vasiliev, A.~V.~Kondakov
\paper About quantifying small color differences in digital images
\jour Computer Optics
\yr 2020
\vol 44
\issue 4
\pages 606--617
\mathnet{http://mi.mathnet.ru/co827}
\crossref{https://doi.org/10.18287/2412-6179-CO-631}
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  • https://www.mathnet.ru/eng/co/v44/i4/p606
  • This publication is cited in the following 4 articles:
    Citing articles in Google Scholar: Russian citations, English citations
    Related articles in Google Scholar: Russian articles, English articles
    Computer Optics
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    References:13
     
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