Ellipse detection via gradient direction in the Hough transform

Detecting ellipses is an important computer vision task. In order to overcome the excessive time and storage requirements associated with the Hough transform, some techniques decompose the required parameter space into several sub-spaces. The decomposition is achieved by using geometric constraints which define relative positions between a set of points. This paper shows how positional constraints can be avoided by using the local properties of the position function to decompose the parameter space. This decomposition requires the combination of a pair of edge points and their gradient direction. The decomposition is used to extract ellipses in synthetic and real images.<
>