An algorithm for measuring texture characteristics by combining Fourier spectra of images obtained in raking light

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Abstract

The article proposes a new algorithm for measuring the texture characteristics of objects in images. The novelty of the algorithm lies in using pairs of images obtained in raking light and combining their Fourier spectra. The application of the developed algorithm is demonstrated in solving the problem of counting the threads of woven bases of paintings from images. A computational experiment showed that the error in measuring the canvas density does not exceed 0.4 threads per centimeter. The accuracy of measuring the canvas density using different methods was compared. The proposed algorithm measures the characteristics of painting canvases with a texture distorted by pollution, ground penetration, or treatment with restoration materials, and is superior in accuracy to previously used algorithms. Using a new algorithm, the density of the canvases of seven paintings from the collection of the State Historical Museum was measured.

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About the authors

A. V. Berezin

State Historical Museum

Author for correspondence.
Email: berezin_aleks@mail.ru
Russian Federation, Moscow

E. Yu. Ivanova

The Ilya Glazunov Russian Academy of Painting, Sculpture and Architecture

Email: ivanova-e-yu@yandex.ru
Russian Federation, Moscow

D. M. Murashov

Federal Research Center "Computer Science and Control", Russian Academy of Sciences

Email: d_murashov@mail.ru
Russian Federation, Moscow

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Supplementary files

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2. Fig. 1. Illustration of the canvas model: a ‒ image constructed using model (1.1) at ; b ‒ Fourier spectrum of image a; c ‒ graphical interpretation of the result of the Radon transform of the Fourier spectrum.

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3. Fig. 2. Example of an image of a painting canvas.

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4. Fig. 3. Image of a canvas treated with a restoration compound.

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5. Fig. 4. Images of a canvas sample under illumination directed: from top to bottom (a); from bottom to top (b).

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6. Fig. 5. Fragment of a canvas image after preliminary processing.

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7. Fig. 6. Combined Fourier spectrum of images of a canvas sample and the result of the spectrum transform: a ‒ Fourier spectrum of the sample image; b ‒ graphical interpretation of the result of the Radon transform of the image of the Fourier spectrum shown in image a.

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