Timeline for Hough Transform not working to recognize a line
Current License: CC BY-SA 4.0
8 events
| when toggle format | what | by | license | comment | |
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| Jan 4, 2019 at 15:02 | comment | added | DrManhattan | Nice, I'm starting to understand. If you move this explanation in detail from the commens to the main answer I will give you the right answer tag :) | |
| Jan 4, 2019 at 14:59 | comment | added | Marcus Müller | well, yes/no! When you've actually got a line, not just two points on a line, the fact that many pixels map onto the same $\rho, \theta$ makes it very robust. If you only got single pixels on each end of a line, there's nothing to accumulate, and yes, then it can only work on exact lines. | |
| Jan 4, 2019 at 14:45 | comment | added | DrManhattan | So, the problem is that the Hough Transform is not able to deal with unprecise alignment of the points and it is expected to detect only ideal lines? | |
| Jan 4, 2019 at 14:37 | comment | added | Marcus Müller | well, good key word: in your $(\rho, \theta)$ space, the upper four points fall onto one point – and everything is fine; however, the last centroid is offset enough from the theoretical line you're looking for that all connections between that centroid and any other centroid maps to a significantly different point in the $(\rho, \theta)$ plane. Hence, there's not enough power accumulating in these four accumulator space points individually for the Hough algorithm you're using to detect a peak. | |
| Jan 4, 2019 at 14:32 | comment | added | DrManhattan | Could you please explain this better? If my understanding of the math behind the Hough trasform is correct if I have no other signal in my image except my 5 points even if the peaks in the $\rho\theta$ space will be dim they will still be very well recognizable, because there is no noise at all to cover the signal of my line. | |
| Jan 4, 2019 at 14:14 | comment | added | Marcus Müller | Well, it doesn't perform well because it's designed to do something different than what you're trying to make it do. There really is only a hint of a line, not a line in your image. | |
| Jan 4, 2019 at 13:36 | comment | added | DrManhattan | Yes, what I already did is exactly a linear fit of the coordinates of these centroids. My question was not about finding an alternative method to the hough transform, but I wanted to understand why the hough trasform method was not working, if there is any kind of improvement I can apply and why there is a difference why I apply it on the simply binarized image and when I apply it with the image with the centroids. | |
| Jan 4, 2019 at 13:23 | history | answered | Marcus Müller | CC BY-SA 4.0 |