Open AccessMeasuring parameters of canvas texture from images of paintings obtained in raking light
Author(s) -
Dmitry Murashov,
Aleksey V. Berezin,
Ekaterina Ivanova
Publication year - 2019
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1368/3/032024
Subject(s) - thresholding , computer science , painting , artificial intelligence , computer vision , texture (cosmology) , computer graphics (images) , process (computing) , image (mathematics) , visual arts , art , operating system
In this work, the problem of threads counting in images of canvases of paintings is considered. Counting of threads is necessary for measuring canvas density and a number of other parameters used by art historians for dating the artworks. We propose to use raking light in the image acquisition process in order to emphasize canvas texture. We modify and adapt known techniques developed for inspecting fabrics in the textile industry. Three threads counting algorithms based on filtering in the Fourier domain and thresholding techniques are proposed and tested. These algorithms for measuring the canvas density from images taken in raking light are efficient in cases when lead white has been used to create the painting, and the analysis of canvas images acquired in X-rays and transmitted light is ineffective. The results of the experiment show that the accuracy of the proposed threads counting algorithms is comparable to the accuracy of known techniques.