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Feature selection and similarity comparison system for identification of unknown paintings

  • Journal of Software Assessment and Valuation
  • Abbr : JSAV
  • 2021, 17(1), pp.17-24
  • DOI : 10.29056/jsav.2021.06.03
  • Publisher : Korea Software Assessment and Valuation Society
  • Research Area : Engineering > Computer Science
  • Received : June 3, 2021
  • Accepted : June 20, 2021
  • Published : June 30, 2021

ParkKyungYeob 1 Joo-Sung Kim 2 Hyun-Soo Kim 2 Dong-Myung Shin 3

1서울과학기술대학교
2엘에스웨어(주)
3엘에스웨어

Accredited

ABSTRACT

There is a problem that unknown paintings are sophisticated in the level of forgery, making it difficult for even experts to determine whether they are genuine or counterfeit. These problems can be suspected of forgery even if the genuine product is submitted, which can lead to a decline in the value of the work and the artist. To address these issues, in this paper, we propose a system to classify chromaticity data among extracted data through objective analysis into quadrants, extracting comparisons and intersections, and estimating authors of unknown paintings using XRF and hyperspectral spectrum data from corresponding points.

Citation status

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