[Insight-users] Circle detection in itk

[Ali -]

Hi Luis,
 
Thanks for the reply, I thought the itk community was dead in the new year.
I need to detect the position and diameter of randomly distributed particle-images where it is assumed each particle-image has a Gaussian profile.  > 1) How fast do you need the circle detection to be ?
The circle detection algorithm must be fast, it is applied to an ensemble of particle-images with Gaussian profile. Each image may contain tens to hundreds of particle-images.
> 2) How big are your images ?
About 1k X 1k. Each particle-image could have a diameter from 3 to 10 pixels.
> 3) Are you looking for full circles ?> or only for circumferences ?
The circle (particle-image) centre and diameter (Gaussian profile diameter) are desirable to be detected.
> > 4) Do you expect to find multiple circles per image ?
As described, yes.
> > 5) Do you have any priori information about the circle ?> (eg. expected positions, expected radius, expected> intensities)
Positions are random, diameters are variable (3 to 10 pixels) the intensities are variable too. The only prior knowledge could be the assumed Gaussian profile of each particle-image. Correlation-based methods may work, but I am sure there are faster methods around. The use of the existing code in the library is preferred.
>> 6) Have you profiled the time that it takes to run the> Hough circle detection in a release (optimized) build ?> 
No, but the following is a quote from 'Practical Algorithms for Image Processing', Seul et al, Cambridge University Press 2000, 4.10.2:
 
'..., and it is for this reason that the Hough transform is far less popular for geometrical objects than the line'.
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