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Use of Digital Technology for the Attribution of Paintings. / Shchegoleva, N. L.; Vaulina, Y. A.

Computational Science and Its Applications- ICCSA 2019 - 19th International Conference, Proceedings. ред. / Sanjay Misra; Osvaldo Gervasi; Beniamino Murgante; Elena Stankova; Vladimir Korkhov; Carmelo Torre; Eufemia Tarantino; Ana Maria A.C. Rocha; David Taniar; Bernady O. Apduhan. Springer Nature, 2019. стр. 792-801 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Том 11622 LNCS).

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Harvard

Shchegoleva, NL & Vaulina, YA 2019, Use of Digital Technology for the Attribution of Paintings. в S Misra, O Gervasi, B Murgante, E Stankova, V Korkhov, C Torre, E Tarantino, AMAC Rocha, D Taniar & BO Apduhan (ред.), Computational Science and Its Applications- ICCSA 2019 - 19th International Conference, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Том. 11622 LNCS, Springer Nature, стр. 792-801, 19th International Conference on Computational Science and Its Applications, ICCSA 2019, Saint Petersburg, Российская Федерация, 1/07/19. https://doi.org/10.1007/978-3-030-24305-0_60

APA

Shchegoleva, N. L., & Vaulina, Y. A. (2019). Use of Digital Technology for the Attribution of Paintings. в S. Misra, O. Gervasi, B. Murgante, E. Stankova, V. Korkhov, C. Torre, E. Tarantino, A. M. A. C. Rocha, D. Taniar, & B. O. Apduhan (Ред.), Computational Science and Its Applications- ICCSA 2019 - 19th International Conference, Proceedings (стр. 792-801). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Том 11622 LNCS). Springer Nature. https://doi.org/10.1007/978-3-030-24305-0_60

Vancouver

Shchegoleva NL, Vaulina YA. Use of Digital Technology for the Attribution of Paintings. в Misra S, Gervasi O, Murgante B, Stankova E, Korkhov V, Torre C, Tarantino E, Rocha AMAC, Taniar D, Apduhan BO, Редакторы, Computational Science and Its Applications- ICCSA 2019 - 19th International Conference, Proceedings. Springer Nature. 2019. стр. 792-801. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-030-24305-0_60

Author

Shchegoleva, N. L. ; Vaulina, Y. A. / Use of Digital Technology for the Attribution of Paintings. Computational Science and Its Applications- ICCSA 2019 - 19th International Conference, Proceedings. Редактор / Sanjay Misra ; Osvaldo Gervasi ; Beniamino Murgante ; Elena Stankova ; Vladimir Korkhov ; Carmelo Torre ; Eufemia Tarantino ; Ana Maria A.C. Rocha ; David Taniar ; Bernady O. Apduhan. Springer Nature, 2019. стр. 792-801 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

BibTeX

@inproceedings{1fc35ababf2e4d4ab36574723d89d6b1,
title = "Use of Digital Technology for the Attribution of Paintings",
abstract = "Modern attribution of art works depends on the expert experience. This implies some subjectivity of his assessments. Recently for making a more informed decision digital image processing techniques have been used. Therefore, the study of the methods for obtaining additional information about the painting, which cannot be obtained using existing methods, is an important task. The joint use of several features extraction methods will allow increase the effectiveness of its analysis. The application developed by the authors based on using of several methods (HOG, DCT, frequency analysis of color, color moments, color histograms, LBP, Gabor filter, GLCM, Hough transform) and allows making an assumption about belonging artwork to a particular art school, style or direction. The results obtained are confirmed by historical data about his teacher and where the artist studied, and who of the masters had the greatest influence on him.",
keywords = "Application for attribution, Attribution of paintings, Color histograms, Color moments, DCT, Digital attribution, Frequency analysis of color, Gabor filter, GLCM, HOG, Hough transform, LBP",
author = "Shchegoleva, {N. L.} and Vaulina, {Y. A.}",
year = "2019",
month = jan,
day = "1",
doi = "10.1007/978-3-030-24305-0_60",
language = "English",
isbn = "9783030243043",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Nature",
pages = "792--801",
editor = "Sanjay Misra and Osvaldo Gervasi and Beniamino Murgante and Elena Stankova and Vladimir Korkhov and Carmelo Torre and Eufemia Tarantino and Rocha, {Ana Maria A.C.} and David Taniar and Apduhan, {Bernady O.}",
booktitle = "Computational Science and Its Applications- ICCSA 2019 - 19th International Conference, Proceedings",
address = "Germany",
note = "19th International Conference on Computational Science and Its Applications, ICCSA 2019 ; Conference date: 01-07-2019 Through 04-07-2019",

}

RIS

TY - GEN

T1 - Use of Digital Technology for the Attribution of Paintings

AU - Shchegoleva, N. L.

AU - Vaulina, Y. A.

N1 - Conference code: 19

PY - 2019/1/1

Y1 - 2019/1/1

N2 - Modern attribution of art works depends on the expert experience. This implies some subjectivity of his assessments. Recently for making a more informed decision digital image processing techniques have been used. Therefore, the study of the methods for obtaining additional information about the painting, which cannot be obtained using existing methods, is an important task. The joint use of several features extraction methods will allow increase the effectiveness of its analysis. The application developed by the authors based on using of several methods (HOG, DCT, frequency analysis of color, color moments, color histograms, LBP, Gabor filter, GLCM, Hough transform) and allows making an assumption about belonging artwork to a particular art school, style or direction. The results obtained are confirmed by historical data about his teacher and where the artist studied, and who of the masters had the greatest influence on him.

AB - Modern attribution of art works depends on the expert experience. This implies some subjectivity of his assessments. Recently for making a more informed decision digital image processing techniques have been used. Therefore, the study of the methods for obtaining additional information about the painting, which cannot be obtained using existing methods, is an important task. The joint use of several features extraction methods will allow increase the effectiveness of its analysis. The application developed by the authors based on using of several methods (HOG, DCT, frequency analysis of color, color moments, color histograms, LBP, Gabor filter, GLCM, Hough transform) and allows making an assumption about belonging artwork to a particular art school, style or direction. The results obtained are confirmed by historical data about his teacher and where the artist studied, and who of the masters had the greatest influence on him.

KW - Application for attribution

KW - Attribution of paintings

KW - Color histograms

KW - Color moments

KW - DCT

KW - Digital attribution

KW - Frequency analysis of color

KW - Gabor filter

KW - GLCM

KW - HOG

KW - Hough transform

KW - LBP

UR - http://www.scopus.com/inward/record.url?scp=85068614615&partnerID=8YFLogxK

UR - http://www.mendeley.com/research/digital-technology-attribution-paintings

U2 - 10.1007/978-3-030-24305-0_60

DO - 10.1007/978-3-030-24305-0_60

M3 - Conference contribution

AN - SCOPUS:85068614615

SN - 9783030243043

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 792

EP - 801

BT - Computational Science and Its Applications- ICCSA 2019 - 19th International Conference, Proceedings

A2 - Misra, Sanjay

A2 - Gervasi, Osvaldo

A2 - Murgante, Beniamino

A2 - Stankova, Elena

A2 - Korkhov, Vladimir

A2 - Torre, Carmelo

A2 - Tarantino, Eufemia

A2 - Rocha, Ana Maria A.C.

A2 - Taniar, David

A2 - Apduhan, Bernady O.

PB - Springer Nature

T2 - 19th International Conference on Computational Science and Its Applications, ICCSA 2019

Y2 - 1 July 2019 through 4 July 2019

ER -

ID: 49224448