Ellipse detection in very noisy environment

Abstract

Ellipse detection is a major issue of image analysis because circles are transformed into ellipses by projective transformations, and most of 3D scenes contain circles that are significant for understanding them (mechanical parts, man-made objects, interior decoration,). Several algorithms have been designed and published, some of them very recently, to characterize ellipses within images and they are very efficient in most classical situations. But they all fail in some specific cases that regularly happen as, for example, when the noise in the image is such as it produces dashed ellipses, or when they are very flat, or when only small parts of them are visible. We propose an algorithm that brings a solution in such cases, even if it is not more efficient than the other ones in classical situations. Hence, it can be used as a complement of other algorithms when we want to detect ellipses in a robust way, i.e. in all situations. This algorithm takes advantage of a property of ellipses related to their tangent lines, without any assumption on edge connectivity: primitives are designed to characterize the possibility for a point and an orientation to locally represent an edge; these primitives are not connected and their global analysis enables to obtain the center location and the three other parameters of ellipses that can be drawn through this set of primitives, i.e. that go through some of these points and that have the corresponding tangent lines. A set of tests has been used to measure its robustness.