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.

Original languageEnglish
Title of host publicationComputational Science and Its Applications- ICCSA 2019 - 19th International Conference, Proceedings
EditorsSanjay Misra, Osvaldo Gervasi, Beniamino Murgante, Elena Stankova, Vladimir Korkhov, Carmelo Torre, Eufemia Tarantino, Ana Maria A.C. Rocha, David Taniar, Bernady O. Apduhan
PublisherSpringer Nature
Pages792-801
Number of pages10
ISBN (Print)9783030243043
DOIs
StatePublished - 1 Jan 2019
Event19th International Conference on Computational Science and Its Applications, ICCSA 2019 - Saint Petersburg, Russian Federation
Duration: 1 Jul 20194 Jul 2019
Conference number: 19

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11622 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference19th International Conference on Computational Science and Its Applications, ICCSA 2019
Abbreviated titleICCSA 2019
Country/TerritoryRussian Federation
CitySaint Petersburg
Period1/07/194/07/19

    Research areas

  • Application for attribution, Attribution of paintings, Color histograms, Color moments, DCT, Digital attribution, Frequency analysis of color, Gabor filter, GLCM, HOG, Hough transform, LBP

    Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

ID: 49224448