Soccer Ball Detection with Isophotes Curvature Analysis

Circle detection is a critical issue in image analysis: it is undoubtedly a fundamental step in different application contexts, among them one of the most challenging is the detection of the ball in soccer game. Hough Transform based circle detector are largely used but there is a large open research area that attempt to provide more effective and less computationally expensive solutions based on randomized approaches, i.e. based on iterative sampling of the edge pixels. To this end, this work presents an ad-hoc randomized iterative work-flow, which exploits geometrical properties of isophotes, the curvature, to identify edge pixels belonging to the ball boundaries; this allow to consider a large amount of edge pixels, but limiting most of the time-consuming computation only on a restricted subset given by pixels with an high probability to lie on a circular structure. The method, coupled with a background suppression algorithm, has been applied to a set of real images acquired by fixed camera providing performances higher than a standard circular Hough transform solver, with a detection rate > 86%.