Algorithms Based on Maximization of the Mutual Information for Measuring Parameters of Canvas Texture from Images
| Autor: | Ekaterina Yu. Ivanova, Dmitry Murashov, Aleksey V. Berezin |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
010407 polymers
Painting Computer science ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Process (computing) 020206 networking & telecommunications 02 engineering and technology Mutual information Maximization Texture (music) 01 natural sciences Thresholding GeneralLiterature_MISCELLANEOUS 0104 chemical sciences Feature (computer vision) 0202 electrical engineering electronic engineering information engineering Image acquisition Algorithm ComputingMethodologies_COMPUTERGRAPHICS |
| Zdroj: | Pattern Recognition. ICPR International Workshops and Challenges ISBN: 9783030688202 ICPR Workshops (5) |
| DOI: | 10.1007/978-3-030-68821-9_7 |
| Popis: | This work deals with the problem of canvas threads counting in images of paintings. 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 improve known techniques developed for inspecting fabrics in the textile industry. Two new threads counting algorithms based on filtering in the Fourier domain and mutual information maximization thresholding techniques are proposed and tested. These algorithms for measuring the canvas density from images taken in raking light are efficient in cases when 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. The analysis of the characteristics of canvases of paintings by F.S. Rokotov allowed obtaining an informative feature that can be used by art historians and experts for dating the artworks. |
| Databáze: | OpenAIRE |
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