Two possible difficulties may occur in the above Hough transform method:
(a) the shape has to be described by an equation, and (b) the number of
parameters (dimensions of the parameter space) may be high. Given the
For each image point with , find the table entry with its
corresponding angle closest to . Then for each of the
) in this table entry, find
All elements in the H table satisfying represent the locations of the shape in the image.
It is desirable to detect a certain 2D shape independent of its orientation and scale, as well as its location. To do so, two additional parameters, a scaling factor and a rotational angle , are needed to describe the shape. Now the Hough space becomes 4-dimensional . The detection algorithm becomes the following:
For each image point with , find the proper table entry with
. Then for each of the pairs (
) in this table entry, do the following for all and :
All elements in the H table satisfying represent the scaling factor , rotation angle of the shape, as well as its reference point location in the image.