By BARBARA WALL
Forgers have been duping the art world for generations, but advances in computer technology may sound the death knell of this illicit industry — and, at the same time, make it easier for collectors of major artworks to know if they are getting what they pay so handsomely for. Eric Postma, a professor of artificial intelligence at Tilburg University in the Netherlands and an expert on the digital analysis of works by Vincent Van Gogh, explains the new technology and why more museums and private buyers should open up their collections to computer scientists.
Q. According to industry estimates, forgeries may account for 10 percent to 50 percent of art for sale on the international market. Which figure is closer to reality?
A. My impression is biased because of the many individuals who have approached me over the years, convinced they own genuine Van Gogh paintings. I estimate that around 99 percent of these paintings are fake or misattributed.
I strongly suspect that the number of forgeries uncovered and publicized each year is just the tip of a very large iceberg. Within the museum world there are two classes of paintings: established works and doubted works. In the first class the majority will be authentic, with perhaps 1 percent forged. In the second class the number of fakes, or misattributions, is much greater — typically, between 50 percent and 80 percent. These figures have not changed much over the years.
Q. Auction houses and art dealers would seem to be the first line of defense in identifying and combating fraud. What steps do they take, and is it enough?
A. Independent art historians will do everything in their power to ensure a work is authentic. However, where price is a motivating factor, subjective judgments can become easily clouded. I firmly believe that auction houses could be doing more to protect client interests by having a more open attitude toward innovations that may help to establish authenticity.
Q. The new techniques are based on computer technology. How can they help distinguish between a fake and the genuine article?
A. An important clue in identifying the artist’s style is the configuration of the brush strokes. Our software is able to break down these brush strokes to find a complex pattern unique to every artist. That is just one of many algorithms we use. We also look at pigment and canvas weave.
Working in cooperation with the Van Gogh Museum and the Kröller-Müller Museum, both located in the Netherlands, we have been able to demonstrate the accuracy of digital analysis. A painting depicting the sea at Saintes-Maries, a Van Gogh fake sold by the German art dealer Otto Wacker, fooled experts for years, but our software easily identified the work as suspect. It had too many prominent brush strokes.
Our methodology was also tested on a U.S. television show, “Nova Science,” where we were easily able to distinguish one fake Van Gogh painting from five genuine works by the artist.
Q. Will digital analysis work on all paintings?
A. We are currently analyzing the works of Rubens, Monet and Gauguin. Provided we have a large enough database of paintings to work from, I see no reason why we could not apply our methods to Old Masters and modern works of art alike.
I was recently asked if we could tell whether a “drip” painting by Jackson Pollock was authentic. Clearly there are no brush strokes to work from here, but Richard Taylor at the University of Oregon performed a fractal analysis of Pollock’s paintings using computer algorithms and succeeded in demonstrating how these algorithms could distinguish a true Pollock from a forgery.
A few artists present challenges. When we started our analysis in 2000, we had trouble authenticating the works of Rembrandt because his paintings are dark and the brush strokes difficult to identify. Technology has improved since then and the digital images that we work from are of a much higher quality.
Ultimately, we would like to come up with an algorithm that goes beyond brush strokes and captures the visual structure of a painting. One art historian refers to the “visual rhythm” of Van Gogh. If we could capture the visual rhythm and other artist-specific features in a software package, it would make the work of art historians much easier.
Q. Despite its advantages in identifying some forgeries, digital analysis is still not widely accepted by the art world. What are the obstacles, and how do you think they can be overcome?
A. We enjoy support from museums in the Netherlands and the United States, but many art historians are still suspicious of our techniques. This is understandable because our algorithms are still being developed. We do not have all the answers, but working together historians and computer scientists would make a formidable team.
We also need to enlarge our database of paintings if we are to offer a full service. I would like to do more work on some of the modern artists, such as Picasso, but many collectors are reluctant to have their expensive works of art held up to scrutiny. Unless we can persuade collectors that it is in the interests of the art world to compile a digitized database of genuine and fake art work, the forgers will always be ahead of the curve.