The orientation matching approach to circular object detection

The paper reports a correlation-based method for the detection of circular objects which is capable of overcoming well-known problems arising from the use of gradient-based voting schemes. Specifically, the method is: (a) capable of detecting circular objects on the basis of both magnitude and direction of the image gradient; and (b) dealing with three-dimensional spherical objects by considering shadows depending on the direction of light. Experimental results on the accuracy of the method and comparisons with the Hough transform and the Hausdorff matching are reported.