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post #11 of 16
bumping before posting results of what the "poster up" suggested?
post #12 of 16
Thread Starter 
Quote:
Originally Posted by Redwoodz View Post
If this is a one time thing seems like it would be faster to just do it manually than you learning how to create a program for it no?
It's weird, in this case the answer is no.

Quote:
Originally Posted by pangeltveit View Post
bumping before posting results of what the "poster up" suggested?
    
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post #13 of 16
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post #14 of 16
As your friend mentioned, OpenCV seems like the natural/best way to go. OpenCV stands for Open Computer Vision, and is essentially a giant set of open source libraries full of functions and classes that are related to image processing. I have used it in the past, and am currently using for my senior design project.

You can download and install OpenCV for a few different languages, however I only have experience with it using C++. As far as learning it, there is some decent documentation on the net that you can use, both on their website and in other places, and a book for sale that goes into it in a lot more detail (which you can find on the net in pdf form).

You can definitely achieve what you are trying to do using OpenCV, but its going to take some work if you have no prior programming experience. If you really want to do this I would say learn some basics of C++ and then start exploring OpenCV for classes/methods that will help you achieve your goal.
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post #15 of 16
I agree with Xazen, without a foundation it's going to be very difficult to do what is a computationally difficult task, which really boils down to identifying noise in a photo.

It also depends on how accurate you need these to be. You can essentially use line distance formulas but those are obviously not lines. I don't have much experience with OpenCV so I don't know if it handles line integrals or not, but it's what needs to happen to get an accurate distance.
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post #16 of 16
delete. and sorry i can't help you.
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