Hello, 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 "/usr/lib/pymodules/python2.6/Cython/Includes/python_version.pxd:31:8: 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 detect circles. * 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. Cheers, Emmanuelle