Shape information is utilized by numerous applications in computer vision, scientific visualization and computer graphics. This paper presents a novel algorithm for exploring and extracting 2D shape information from greyscale images with no a priori information about the objects represented. From an image, our algorithm outputs the intensity range spanned by each significant object as well as a versatile shape model of the object that is directly useful for many applications. The technique introduced is based on the computation of the shape gradient, a numerical value for the difference in shape. In this case, the difference in shape is caused by the change in threshold value applied to the image. The use of this gradient allows us to determine significant shape change events in the evolution of object forms as the threshold varies. Our algorithm uses the Union of Circles shape representation, which is flexible, stable and has an effective shape metric. The extraction method is conseq...
Roger C. Tam, Alain Fournier