Photo: ANP / “Sunset at Montmajour” by Vincent van Gogh
The study was published in the June issue of the journal *Surface Topography: Metrology and Properties*. Its authors are François Berkmans, Ludovic Nis, and Maxence Bigerel from the University of Technology of Hauts-de-France in Valenciennes, France.
The method is based on high-precision scanning of the painting’s surface. The technology captures the finest details of the paint layer’s texture and analyzes the unique surface pattern using mathematical algorithms. According to the researchers, such details are virtually impossible to distinguish with the naked eye, yet they may contain characteristic signs of a particular artist’s creative style.
The problem of forgeries remains one of the most pressing issues in the global art market. Disputes over the authorship of individual works can drag on for years, and errors in attribution can cost collectors and museums millions of dollars. That is why the search for objective scientific methods to verify authenticity remains a top priority for experts.
To test their technology, the researchers analyzed digital scans of nine Van Gogh paintings. They then tested the method on two disputed works. In one case, the system identified a known forgery by detecting significant deviations from the artist’s characteristic technique. In the second case, the analysis results coincided with the conclusions of experts regarding the painting “Sunset at Montmajour,” whose authenticity was confirmed by the Van Gogh Museum in 2013 after years of debate among specialists.
The authors emphasize that the new technology will not replace traditional art historical expertise but will serve as a complement to it. As Berkmans noted, the method allows for obtaining a “measurable imprint of the artist’s brushstroke” without taking samples or interfering with the structure of the work.
If widely adopted, the technology could become a new standard for preliminary verification of artworks, complementing traditional methods of expertise and reducing the risk of costly errors in the global art market.
