In the Hough transform, the votes give a good indication of how likely a certain pair of r and θ represent a line. But depending on the thickness and straightness of the lines in the image, the Hough transform can return multiple pairs of r and θ that represent lines that are very similar to each (i.e. colinear lines). We can then cluster the r and θ pairs into groups (especially useful when we know how many lines there are in the image), and use the centers of each group to get a mean line. But it would be even better to have the votes per pair of r and θ so that we can weigh the r and θ estimates accordingly when calculating the mean per group (and/or even before, during the clustering).
In the Hough transform, the votes give a good indication of how likely a certain pair of
randθrepresent a line. But depending on the thickness and straightness of the lines in the image, the Hough transform can return multiple pairs ofrandθthat represent lines that are very similar to each (i.e. colinear lines). We can then cluster therandθpairs into groups (especially useful when we know how many lines there are in the image), and use the centers of each group to get a mean line. But it would be even better to have the votes per pair ofrandθso that we can weigh therandθestimates accordingly when calculating the mean per group (and/or even before, during the clustering).