Comments (5)
I totally agree.
I'll give it a shot ASAP.
from imagefeatures.jl.
The Hough transform doesn't require that a line be continuous; take a few pixels out of the middle, and you get almost exactly the same transform. That's actually part of its point, it can identify lines in noisy images. So what does "per line" actually mean?
from imagefeatures.jl.
I mixed the terminologies, where "lines" should have been "pairs of r
and θ
". I've now edited my post, and hope it's clearer. My main point was that having access to the votes helps analyzing which pairs of r
and θ
belong to which line in the image and what their contribution to that line is. This knowledge can help improve the line estimates.
from imagefeatures.jl.
Maybe more generally, I think the current implementation mixes two things: I think there's a strong case to be made that accumulator_matrix
is the Hough transform, and that what's currently being returned is the result of some analysis of the transform. Want to take a crack at a better API? Breaking changes are totally fine, we'll just bump the minor version number.
from imagefeatures.jl.
So I took a look, and while it should be straight forward to separate between generating the accumulator_matrix
and the specific method of detecting line-candidates, I can't find a ρ
range. There is a range for the angles, but not for the distances. Is this an implementation detail, and it's simply range(0, step = stepsize, length = numrho + 2)
, or is it because the distances are different per angle?
It's worth mentioning that the current implementation is pretty smart about avoiding saving a large matrix of useless r
and θ
pairs. So in that respect it seems like a shame to move away from that efficiency... With that in mind, maybe it would be good to simply add the vote value to each rθ
pair, opening up the possibility to the kind of post-analysis I mentioned above. I'll give that a look.
from imagefeatures.jl.
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from imagefeatures.jl.