Detecting Faked Photographs Gets Easier 258
nusratt writes "Some years ago, an issue of 'Whole Earth' had a convincing cover-photo of a flying saucer cruising low over downtown San Francisco in broad daylight. The accompanying feature article proclaimed that photographs can no longer be trusted as evidence of anything, because of the ease of doctoring images digitally and undetectably. Now, Dartmouth Professor Hany Farid and graduate student Alin Popescu 'have developed a mathematical technique to tell the difference between a "real" image and one that's been fiddled with.' Farid says, 'as more authentication tools are developed it will become increasingly more difficult to create convincing digital forgeries'." There's also an NYT story.
Seamless Math Next? (Score:5, Interesting)
1. Forgers get smart and use older cameras to take a picture of a digital forgery to pass as an original, using blurring techniques offered by physical means and lens... etc (easy)
2. Forgers quit being forgers (unlikely)
3. Alteration technologists create armor against image forgery detection algorithms (possible)
For me, I think any time spent trying to beat the detection of forgeries would be a good thing in terms of art and creativity -- not to mention the possibility of better digital growth algorithms to join layers mathematically seamlessly (which could be used in games and simulation engines for better realism). However, law enforcement agencies might try to combat the circumvention of forgery detection by charging people with crimes for only trying to make their images more realistic and improve technology. It's a messy issue, that will sort itself out over time.
In Doom 3 Bloopers, a mod I've started on, I am looking at ways of integrating realworld imagery into the mod, and this detection stuff could actually help me to better integrate my own art and images if I can find a way around it. Let's face it, if the math says it's an original, the human eye will be fooled, which is the goal of most video game design. If anyone wants to help along those lines, they should contact me [zenbuzz.org]!
Actually... (Score:5, Interesting)
Random set of pixels? (Score:2, Interesting)
Okay, but here's my question. (Score:4, Interesting)
That makes sense. However, it seems like these statistics would be based on very minor details. What happens if you run their analyzer on an image that has been altered by using lossy image compression, such as JPEG compression? [conjoineddreams.net] Lossy image compression is designed to obliterate details humans wouldn't notice; some of these details might be significant to their statistical model. Would JPEG-compressing an image make it impossible to determine its veracity? Would their software just tag all JPEG images with compression below a certain threshold as being "unnatural" (since they have been, after all, digitally altered-- just not digitally altered in a content-relevant way...)
And don't some digital cameras use lossy formats such as JPEG as their native storage format?
Re:What kind of digitized photos does this work on (Score:2, Interesting)
Smudging a part of an image would remove these artifacts, and would be near impossible to reproduce - like the paper grain on a canvass oil painting.
Admissibility of Digital photographs as evidence? (Score:5, Interesting)
Re:Seamless Math Next? (Score:5, Interesting)
Why wouldn't someone simply build a filter into a program that changed bits in an image until it passed a check by their algorithm - on failing, it would simply go back and change more appropriate bits?
Seems as though it would be a computationally intensive but a logically easy task.
reverse-engineering? (Score:2, Interesting)
Re:Okay, but here's my question. (Score:3, Interesting)
Of course, you could just save the doctored foto itself as a low-quality JPEG - but a) if it's going in a newspaper, do you want low quality?, and b) you're still just adding your own artifacts to the original - it's going to be some pretty severe compression before they're undetectable.
Re:MICHAEL, thanks for adding the . . . (Score:4, Interesting)
If A doesn't conform to the statistical distribution of B, then A isn't B (with a high degree of confidence). But if does, that doesn't mean it is B -- you might just be looking at the wrong set of identifying features. I.e. not everything with two feet and a bill is an aquatic bird; it might be the waiter.
and from the obvious paranoid side... (Score:2, Interesting)
On the other hand, it would be nice to go back and look at a lot of older photos to see what's what with them now.
Lately there's a smidgen of controversy over some of the mars photos, this would be a great place to use the technique.
Re:Seamless Math Next? (Score:4, Interesting)
Don't be so sure about that!
I don't know what these researchers are doing, but I can venture a guess. You can think of an image as being composed of a large set of superimposed sine waves---they look like this [ouhk.edu.hk]. To figure out what sine waves make up an image, you do a Fourier Transform, which is well documented on Google.
Natural images contain a characteristic power spectrum: some frequencies--lower ones--tend to occur quite often, while others--higher frequencies--are less common. The spectrum is actually pretty regular across an image set. I'm betting, though, that fake images don't respect this power spectrum and lead to detectable anomalies.
But beware! You can have completely bogus images that also respect the power spectrum. Some researchers at MIT (Torralba et al.) use power spectra to successfully detect different image environments, e.g. indoors, outside in a city, out in the country, etc., but in the papers they show some images that have been reconstructed from their spectral models.
You would not be fooled. They look like finger paint pictures.
--Tom
Re:What kind of digitized photos does this work on (Score:3, Interesting)
One wonders whether this will lead to a legal distinction between lossily compressed images and others. While audiophiles have long been ape for lossless compression, not as much a need has been felt for graphics. Where do lossless graphic compression efforts stand? Is this an area where a proprietary standard might lead to big $$$?
Re:Self Defeating (Score:4, Interesting)
Effect on Steganography? (Score:1, Interesting)
Re:Why not *make* it real? (Score:3, Interesting)
The short answer is dot structure. All printers, (excepting Dye Sub) use some form of sparying of ink, or layering of screened images(halftone dots) Fancier does not necessarily mean smaller dots, it usually means more calibrateable and more consistent color. What you need is a film recorder, which will transfer your image to a negative or a slide, and currently, there are no digital cameras that will record an image at a high enough resolution for this to be flawless (about 40-100 pixels per millimeter), so you must start with a film camera and scan the image in at a high enough resolution. The typical rule of thumb for this kind of work would be one size up from what your end result would be. So if I wanted to create a faked 35mm slide, I would start by taking pictures with a 4x5" film camera scan and use that.
But yes, your point is sound. Technology will not fill the analog hole. Even in "digital" photography.
Re:Seamless Math Next? (Score:5, Interesting)
Or you could realize there's inherent error in any statistical method, and that with a little bitof foresight, this error could be expoited to provide false results. The best detector of falsified photography is still a well-trained human eye. The key to knowing whether or not to trust images is to train your eye.
Re:Seamless Math Next? (Score:4, Interesting)
One example photo from the beginning of the last century or before, depicted two figures by a lamppost on a foggy Parisian street. I took it for an unaltered print, but it turned out to be a composite of seven [!] separate images. It was laboriously done in the darkroom. It was incredible. (Unfortunately, I can't find the specific photo on their otherwise excellent site.)
Now, we've all seen great darkroom manipulation like the work of Jerry Uelsman (www.uelsman.net), but this particular picture was a hundred years older than his work. It was absolutely convincing.
I guess my point is, photographs have in fact been "faked" as long as there have been photographs.
Re:Seamless Math Next? (Score:1, Interesting)
mixture of some of the same, this will further excacerbate the differences. A 'foto analyst' will probably have no 'reference foto' of any particular subject matter. Such 'reference will have to come from the same camera as the study foto on order to reproduce reasonably the same shot for many reasons
including but not limited to lens defects, exposure program duplication, timeing, operator shake of the camera, and other reasons...
For these reasons, the idea that some mathmatician can calculate a fake with statistics is patently fatuous! Any believer in this would be a fool. Many fools exist in governments however. They are called 'civil service'. Many more are in private industry. These worthies are called 'executives'.
I know of what I speak. I have a minor in math
and over 190 credit hours on my Bachelors in Engineering. This record includes statistics. I love to work in digital images. Instead of looking for 'checksumsin the dark' which is for dorks, look instead for small cut lines to detect cut in images. Most image parts should kind of fade into the other parts of the image. If this border is sharp, then that part may be added, especially if the focus is much different for similar image parts in other parts of the larger image. For this one requires a human so far, and still the results will be inexact, and would not hold up in a fair court where 'beyond a doubt' is the criterion of proof. For some civil cases where 'preponderance of evidence' is the standard, this still would be unreliable unless corroborated with other evidence.
In the old days of typewriter forgeries, one could literally 'fingerprint' the typewriter. Now
one can take a pic, take another. Cut out an image on a 'blue screen' and digitally add it to the other image in a third working final. Then one could print the third on a high definition printer. This print can be run through a color scanner at a slightly lower resolution as the original, and the process done over and over until
the result looks like a slightly degraded original shot. Here the repeated scannings will add just enough fuzz around all the image parts as tho make the whole 'all new again'!
Different goal (Score:1, Interesting)
On the other hand, all the Farid's technical papers mentioned on his page (linked several posts above) seam to deal with the forgery detection, the detection of steganography being targetted only in several press releases. May be the forgery detection is the first step, the only to be actually taken yet. Or may be the algorithms targetting directly the main goal are kept secret.