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Sat Jul 12 13:49:32 CEST 2008

## Toroidal Hough Transform

For grid estimation, we're not really interested in individual maxima
on the r-spectrum. Reducing this spectrum to a couple of values can be
done by adding bias toward a period R. Then, instead of using a voting
algorithm for bundles:
(r,t) | r = x cos t + y cos t, t \in [0,pi]
we vote for the phasor:
(e^{i r/R} , t)
The advantage is that these votes can be accumulated immediately, so
memory access becomes simpler, and a histogram interval discretization
step is not necesesary.
The core computation is the evaluation of cos/sin, the rest seems
memory-bound.
Given R and t, the grid period, compute the complex phasor p:
p(R,t) = \sum_n e^{i r_n(t) / R}
r_n(t) = (x,y) ? x cos t + y cos t : 0
The inner loop is the sum over the exponentials of r_n(t) for linearly
increasing x with y fixed, so this can be updated.
However, the image will be mostly sparse, so this will probably not
bring much speedup (points are not equidistant, so multiple rotation
update matrices are necessary).
( Tests indicate the 2 approachs: straight eval + update are about the
same speed. Maybe it's memory bound? )

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