Efficient computation of various types of skeletons

The skeleton transformation is particularly useful in the field of image processing and may be computed by various techniques. This paper describes a new skeleton algorithm, which is based on the original concept of anchor point, i.e. of point that the skeleton is bound to contain. Its first step consists in extracting the desired anchor points. Then, the set X to skeletonize is progressively thinned in such a way that, on the one hand, the anchor points can never be removed and on the other hand, the homotopy of X cannot be modified. This operation is efficiently implemented thanks to a queue of pixels. The algorithm turns out to be extremely efficient and accurate on conventional computers. Furthermore, it allows to deal not only with standard skeletons, but also with such objects as minimal skeletons, homotopic markings, smoothed and pruned skeletons, etc. Its flexibility is also proved by the facts that it works both in the Euclidean and the geodesic cases, that its adaptation to any kind of grid is straight forward and that it can even be extend to n-dimensional images and to graphs skeletons in image analysis and shape recognition.