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Registered Member #1062
Joined: Tue Oct 16 2007, 02:01AM
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Posts: 1529
If I have an image:
And I want to pick out points, labeled here (with contrast adjusted of the image):
Which are basically the "bumps", what kind of neural network would i use? Or is this even suitable for neural networks?
I am thinking of using a Hopfield Network (similar to OCR?). However, how do i choose the amount of neurons? What is actually the input? The image pixels?
I plan on using Encog (for Java) to make a program to pick out these points, and i plan on using a Hopfield+levanberg (or backpropagation) network. However, i Can't find any good resources for image processing with Neural Networks.
Registered Member #65
Joined: Thu Feb 09 2006, 06:43AM
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Posts: 1155
on-board Morphological and SLAM operations are currently computationally unfeasible for small UAVs.
However, there are exotic motion tracking cams built for noisy environments:
Perhaps a better question is... what precisely are you trying to accomplish? i.e. Sobel edge detection is more efficient than most blob detection routines:
Registered Member #2140
Joined: Tue May 26 2009, 09:16PM
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Posts: 53
This is actually unrelated to the UAV. I am simply trying to count the amount of "bumps", or dislocations. The picture you are seeing is about 4 micrometers across, of galium nitride growth. This has to do with my internship at the NRL.
As for the UAV, I am actually recieving a couple Cent-eye sensors, and have the change to test them out.
Registered Member #65
Joined: Thu Feb 09 2006, 06:43AM
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Interesting, you could try a simple filter, find center of each contiguous area, and add a point tracker. See OpenCV/samples/c/lkdemo.c for an example of automated feature position tracking.
Registered Member #2140
Joined: Tue May 26 2009, 09:16PM
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Posts: 53
I have actually got very close to what you got. However, the problem is detecting the points after that. If i were to do it myself, I would use flood fill. Instead, I have been trying to use the OpenCV blob detection, which should be perfect for this. However, the blob count seems to be capping at 257, even though there is an argument for the number of blobs.
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Image Feature Extraction
