Good day everyone,
Sorry if this should be obvious to me, but: will a person be holding the cell phone? Is it a running video recording of a room. If not, are the cell phones on a table? A rolling assembly line that stops for you to take a snap shot? If it's a snap shot like that, can you control the orientation of the cell phone? If you have no control over the orientation ofthe cell phone, you'll need to use image recognition to recognize the orientation I think, and then you need to capture the stick image. Is the sticker image designed to be easily recognized by such a sad software, do you have a clear shot with the camera?
You describe a very difficult problem. Slightest varriations in orientation, lighting, distance, etc. cause one photo to be completely different than another (same goes for video). This is not a solved problem by any means, and has active research taking place in the academic and coorporate communities. If the picture is not a close up, then the current state of the art wouldn't really be able to tell. It would determine that the two pictures were close (due to the surroundings) and thus the same image (with or without a sticker on the phone). On the other hand, if it's a zoomed in image, and you can't control all aspects as described earlier, then even if the sticker exists in two photos, there is a significant probability that they will be different enough that the images are marked different (see the problem?). Either way controlling or non-controlling the state of the art I would guess could give you at best 70 to 80 perecent accuracy. If that's good enough, than you might want to see what's out there in the academic community. I don't think coorporations will want to dole out their research on that one.
If this is an assembly line, it seems to me like you'd have a degree of control over the sticker, in which case get a bar code placed, then put a laser reader in.
This sounds like a perfect project for the open source community! It's just the sort of challenge bright minds would want to sink their teeth into - and could be a great resume builder if they solve the problem.
MIT, and other unis, are working on something called augmented reality. Basically they are looking for ways to make machine recognization of our world a lot easier and more common. Sometimes it's through brute force, throw a lot of computation at it and see if it can recognize something only humans can. Or they theorize as to what expect we should design a society that aids this recognition: like barcodes, radio tagging, and other guides integrated to the world around us.
Have a look at http://www.skylinetools.com/imagelib/index.html they may have something useful. Note that it is not cheap.
I believe there exists quite a few programs which can handle this. Its is very common to have optical inspection systems in modern assembly lines. Try a google search on "machine vision" or "automatic optical inspection". I wouldn't recommend writing such an application from scratch if you are not an image processing expert.
I did a class on image recognition (which I promptly forgot).
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