Requested features

WARNING:

This page is updated infrequently, and does not always reflect our current top priorities. Please refer to the Feature request issue tag instead.

Before adding a new feature, please discuss it on the developer forum first.

Administrative and web

• Port website to Hugo (ask Stéfan for details)
• Get interactive gallery running again
• Add survey to website (see e.g. https://getsitecontrol.com/)

Implement Algorithms

• Rotational symmetry feature detectors (see Ch 4 of Björn Johansson's thesis, Low Level Operations and Learning in Computer Vision)
• Add Eldad Afik's ring detector
• Add BM3D denoising (see also IPOL publication)
• Enhanced Correlation Coefficient (useful for registration)
• Contour following as described in Suzuki, S. and Abe, K., "Topological Structural Analysis of Digitized Binary Images by Border Following". CVGIP 30 1, pp 32-46 (1985).
• Unify image registration
• COSFIRE [see also George Azzopardi's publications]
• Fast Radon Transform
  • Brady, "A Fast Discrete Approximation Algorithm for the Radon Transform", SIAM J. Comput., 27(1), 2006
  • A fast digital Radon transform--An efficient means for evaluating the Hough transform WA Götz, HJ Druckmüller - Pattern Recognition, 1996
• Fast 2D convex hull (consider using CellProfiler version). Algorithm overview. One free implementation. (Compare against current implementation.)
• Blurring kernel estimation; also see this paper
• Blob Detection
  • Laplacian of Gaussian(LoG)
  • Difference of Gaussians(DoG)
  • Determinant of Hessian
  • Hessian Laplace
  • Maximally stable extremum regions(MSER) [in progress by Vighnesh]

Drawing (directly on an ndarray)

• Text rendering using matplotlib another example; See #877

Adapt existing code for use

These snippets and packages have already been written. Some need to be modified to work as part of the scikit, others may be lacking in documentation or tests.

• 2D image warping via thin-plate splines [ask Zach Pincus]

Rework linear filters

• Should take kernel or function for parameter (currently only takes function)
• Kernel shape should be specifiable (currently defaults to image shape)
• Fast, SSE2 convolution (see prototype in pull requests) [let's see where LLVM + GPU frameworks go]
• Correlation with sparse kernels

docs

• Finish up interactive Docker gallery
• Add examples to the gallery
• Write topics for the user guide.