Which is the fastest method to extract a rough orientation statistics from images. I think the most precise way is the scanning with local Gabor filters, but its very time consuming. Is it possible to use some kind of global transformations or filters? Fourier transformation can help in this case? If it helps, I can fix the wavelength.

  • $\begingroup$ what sort of orientation statistics? can you give a bit more information about it? $\endgroup$ – Seyhmus Güngören Feb 18 '15 at 16:26
  • $\begingroup$ frequency of local gratings/edges/Gabor patches etc. as a function of orientation angle $\endgroup$ – sceptic Feb 18 '15 at 21:06
  • $\begingroup$ I don't know that it's the simplest, but curvelets (and other wavelet-type) transforms can be used to characterize orientation. $\endgroup$ – AnonSubmitter85 Feb 26 '15 at 19:59

There is Hough transform. conceptually simple but computationally still demanding. In engineering it is fairly a standard tool to locate the objects.


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