as I'm using both Python/Scipy and image processing in my daily
work, I would be interested in contributing to the image scikit if I can
be of any help.
I have read the "Contribute" page of the website, and maybe the
easiest way to start me off would be that I write some documentation and
tests. But please tell me if you have other suggestions, I do not have
specific preferences. The only thing is that I have almost never used
Cython, but I'm willing to learn it.
By the way, I had trouble installing the scikit as with my
Ubuntu-packaged version of Cython (0.11) I got lots of errors (such as
Buffer types only allowed as function local variables") and I had to
install Cython 0.12 to make it work. I can provide the whole log if you
expected the install to work with Cython 0.11.
In the longer term, I could also contribute two algorithms that I
have implemented in Python (with dependencies to numpy and scipy):
* the circular Hough transform (for 2-D images) that may be used to
* a "random walker" segmentation algorithm that implements a recent
generic algorithm by L. Grady [Random walks for image segmentation, Leo
Grady, IEEE Trans Pattern Anal Mach Intell. 2006 Nov;28(11):1768-83]. The
algorithm basically finds the region into which given markers
preferentially diffuse, with an anisotropic diffusion that penalizes
diffusion across strong gradients. I use it to segment huge (500x500x500)
3-D tomography images that are very noisy and full of artifacts and the
results are quite satisfying (much better than what I can get with a
watershed, for example).
But I think it is wiser that I first get to know the project by
contributing to existing parts of the scikit.
Let me know how I can help.