|
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 (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
|
RSS/XML Feed