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What's real, what's phony?

Published July 26, 2004

New algorithm identifies digital photos that have been altered

"Seeing is no longer believing. Actually, what you see is largely irrelevant," says Hany Farid. He is referring to the digital images that appear everywhere: in newspapers, on websites, in advertising, and in business materials, for example.

Hany Farid
Hany Farid (Photo by Joseph Mehling '69)

Farid and Dartmouth graduate student Alin Popescu have developed a mathematical technique to tell the difference between a "real" image and one that's been fiddled with. Consider a photo of two competing CEOs talking over a document labeled "confidential - merger," or a photo of Saddam Hussein shaking hands with Osama bin Laden. The Dartmouth algorithm, presented recently at the sixth International Workshop on Information Hiding, in Toronto, Canada, can determine if someone has manipulated the photos, like blending two photos into one, or adding or taking away objects or people in an image.

"Commercially available software makes it easy to alter digital photos," says Farid, Associate Professor of Computer Science. "Sometimes this seemingly harmless talent is used to influence public opinion and trust, especially when altered photos are used in news reports."

Photos have been altered in the past, from airbrushing in fashion magazines, to aliens in tabloid newspapers, to giant lizards in the movies, but computers make it easier for more and more people to manipulate images. Farid explains that "regular" photos are hard to change without special expertise in altering negatives or dark room privileges that would allow someone to influence the printing process. However, once images have been digitized, translated into the computer language of ones and zeros, it's easier to manipulate them.

A digital image is a collection of pixels or dots, and each pixel contains numbers that correspond to a color or brightness value. When marrying two images to make one convincing composite, you have to alter pixels. They have to be stretched, shaded, twisted and otherwise changed. The end result is, more often than not, a realistic, believable image.

Which photo was doctored, and how can you tell? The image on the left is the original photo, and the image on the right is the altered one. Hany Farid's algorithm makes it possible to mathematically determine whether a photo has been tampered with. (IMAGES COURTESY OF HANY FARID)

"With today's technology, it's not easy to look at an image these days and decide if it's real or not," says Farid. "We look, however, at the underlying code of the image for clues of tampering."

Farid's algorithm looks for the evidence inevitably left behind after image tinkering. Statistical clues lurk in all digital images, and the ones that have been tampered with contain altered statistics.

"Natural digital photographs aren't random," he says. "In the same way that placing a monkey in front of a typewriter is unlikely to produce a play by Shakespeare, a random set of pixels thrown on a page is unlikely to yield a natural image. It means that there are underlying statistics and regularities in naturally occurring images."

Farid and his students have built a statistical model that captures the mathematical regularities inherent in natural images. Because these statistics fundamentally change when images are altered, the model can be used to detect digital tampering.

"This technology to manipulate and change digital media is developing at an incredible rate," says Farid. "But our ability to contend with its ramifications is still in the Dark Ages. I'm always asked if this technology would stand up in a court of law." He explains that the simple answer is, "eventually." Farid predicts there will be skepticism and a great deal of scientific and legal debate. But eventually, he believes that some form of his technology or someone else's will be incorporated into our legal system.

Farid, whose research is funded by an Alfred P. Sloan Fellowship, the National Science Foundation and the U.S. Department of Homeland Security, also works with law enforcement officials, government representatives, and corporate leaders on this issue of authenticating digital images. This research is part of Dartmouth's Institute for Security Technology Studies.

 "There is little doubt that counter-measures will be developed to foil our detection schemes," says Farid. "Our hope, however, is that as more authentication tools are developed it will become increasingly more difficult to create convincing digital forgeries."

By SUSAN KNAPP

Questions or comments about this article? We welcome your feedback.

Last Updated: 12/17/08