From: <HIDDEN>
Newsgroups: comp.soft-sys.matlab
Subject: Re: How to calculate the angle between two images?
Date: Fri, 3 Apr 2009 12:07:01 +0000 (UTC)
Organization: STFC Rutherford Appleton Laboratory
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"khoo" <> wrote in message <gr4ten$oks$>...
> Hi all, currently i face the problem to find the rotation angle...i got one image is rotate in unknown angle compare with the original image, but i not have idea how to calculate the angle cause the angle is a variable angle..can anyone senior teach me here,...need it urgently...and i quite noob in image processing..

One method that I found for easily determining the relative 
angle of 'twist' between a known reference image  and a rotated image was accomplished very reliably even for arbitrary images.

1) Compute the vertical and horizontal gradient of every 
2) Use the atan2 function to convert the image to an angle 
image. Note that pixels on a featureless region returns 
angles that are purely dictated by noise.
3) Calculate an edge image - using edge, Canny is a good 
choice, but Sobel will probably work - depending on the 
complexity of the image.
4) Fatten up the edge lines using morphology operators 
dilate/erode. Binarize into a mask image
5) Mask the angle image with above mask, thus removing 
meaningless angle pixels. We are only looking at gradients 
that are real.
6) Apply this to the reference image, and the target image
7) Histogram the results. Remember as the pixels represent 
angles, the histogram essentially wraps round 0 mapping to 
2Pi radians.
8) Compare the histograms, I found correlation a good way 
to do this, the peak on the correlogram provides you with 
the relative rotation between the two images.

One danger point is that if your image suffers badly from 
digital stepping (aliasing) you can get peaks at 0 and 90 
degrees on both images. So you need to do something 
intelligent at removing this from your histograms prior to 
doing your comparison.

One of the fun things that I tried, was to use fast 
correlation to do the matching. I FFT'd both histograms, 
then extended the spectra by zero packing, done the 
multiplication in the frequency domain, then followed up by 
the IFFT. This generated a very nicely interpolated measure 
of the relative rotation between the two images.

Hope that this is helpful, and makes sense


Dave Robinson