A nonparametric approach for detecting lines and curves
G. Lim, Michael D. Alder · 2002
The process of detecting lines and curves in an image is an important component of many pattern recognition and computer vision applications. There are well understood approaches to finding curves from a parametrised space of curves. In many practical cases, however, there exist arbitrary shape curves, and different types of curves in the same image. In addition, local perturbation noise can be added to the images. We propose a nonparametric method to overcome the above mentioned problems. The method is based on local modeling of the data. It does not require the specification of a parametric space of curves. It can be used to detect arbitrary curves and thus has a wider applicability than parametric approaches.