Sep
29
2009

They say the Computers say no, but that is not what I read.

The ability of computers to analyze complex digital images is growing rapidly. Robots are being fitted with powerful vision systems that enable them to recognize and hold things.

Computers can scan satellite images of the Earth for tiny features, or search pictures from deep space for strange objects. They can analyze medical images to find out what might be going on inside a human body. Now digital imaging is starting to figure out how to spot art forgeries, too.

Science has long been used to help authenticate works of art. Technicians can date paint from its chemical composition, for example, or x-ray a canvas to reveal what lies below the surface. In recent years, however, the art itself has come under more scientific scrutiny, especially through the analysis of brushstrokes. The idea is to establish an artist's 'handwriting' to help experts attribute paintings.

One of the most comprehensive studies using such methods was published recently in Signal Processing Magazine, published by the Institute of Electrical and Electronics Engineers. James Wang of Penn State University and his colleagues from other universities analyzed the paintings of Vincent van Gogh, with the assistance of the Van Gogh and Kroller-Muller museums in the Netherlands.

The researchers used high-resolution images, made in shades of grey, of 101 paintings which were either by Van Gogh or in his style. Of these, 82 have consistently been attributed to the Dutch painter, and a further six are known to have been painted by others. (Experts cannot agree who painted the remaining 13 pictures.)

From these paintings, 23 were selected because they were known unquestionably to be by Van Gogh and because they represented different periods of his life, during which his style changed. These paintings were used to 'train' computers running image-analysis software about how the artist painted. Scans of small areas of the paintings were taken for individual analysis, so the software could identify the recurrent use of certain brushstroke patterns and other features. The resulting data were used to build a mathematical model of Van Gogh's style against which the other paintings could be tested.

The model had some success. For instance, when two known Van Goghs, 'The Plough and the Harrow' and 'Wheatfield with Crows', were used for training, the system indicated that among the paintings that closely resembled them was 'The Sea at Saintes-Maries', a fake commissioned or sold by Otto Wacker, a German art dealer. But when the image analysis was repeated at a greater level of detail, the Wacker forgery was shown to be different. Ultimately the software correctly identified four of the six paintings known not to be by Van Gogh, though it also classified two of his works as having been painted by someone else.

The researchers describe their results so far as 'encouraging, but not perfect'. Computerized image-processing systems should get better at detecting forgeries as they are trained to recognize further aspects of artists' styles, says Wang. He and his colleagues are now using images taken at other wavelengths, including ultraviolet, to analyse different aspects of Van Gogh's brushwork.

Interest has been shown in using image analysis to help find forgeries of other artists. The bigger the body of an artist's known work, the more accurate the system should be, because it will have more examples to learn from. But however good computers get at classifying paintings, they are likely to remain only one of the tools used to detect forgeries. Although the researchers are certain that technology can provide some answers to riddles about whose hand was responsible for a particular work, they also concede that human experts will have the final say.

Your Comments, Thoughts, Questions, Ideas

JGordon's picture
JGordon says:

It looks like you're responding to another article, vanrijngo. You've got an interesting take on this new technology, but it took me a second to realize that you had your own thoughts in addition to the text of the other article. Could you cite the article, and provide a link?

Also, if you use blockquotes, you can set your text apart from the other author's. By typing "< blockquote >" (without the spaces) at the beginning of a section of text, and "< /blockquote >" (again, without those spaces) at the end, you can make a big piece of quoted article look like this:

"This is a fake quote I'm making up as an example. Look how well it stands out from the rest of the post!"

Not a big deal, but it can be a helpful tool.

posted on Tue, 09/29/2009 - 4:49pm
KIDO's picture
KIDO says:

Here is the link you ask for JGorgon. Thank for your help and information,...

http://in.biz.yahoo.com/080817/203/6wmfi.html

posted on Wed, 09/30/2009 - 3:18pm

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