Robust and time-efficient skeletonization of a (planar) shape, which is connectivity preserving and based on Euclidean metrics, can be achieved by first regularizing the Voronoi diagram (VD) of a shape's boundary points, i.e., by removal of noise-sensitive parts of the tessellation and then by establishing a hierarchic organization of skeleton constituents. Each component of the VD is attributed with a measure of prominence which exhibits the expected invariance under geometric transformations and noise. The second processing step, a hierarchic clustering of skeleton branches, leads to a multiresolution representation of the skeleton, termed skeleton pyramid.

O(1) scan operations

Broadcasting (one-to-all) and gossiping (all-to-all) are two major communication paradigms that were considered from both practical and theoretical points of view. Indeed, such communication patterns frequently appear in parallel programming, and therefore are included in most of the communication libraries (e.g., MPI or PVM). Also, broadcasting and gossiping times of graphs are important parameters yielding lots of fundamental results. For most of the communication models, the corresponding decision problems are NP-complete in general. Therefore, in this paper, we consider broadcasting and gossiping heuristics. We study the performances of several heuristics applied to partial meshes, that is to connected subgraphs of the mesh. This choice of topology is motivated by the fact that a regularly connected multicomputer can be shared by many users, each of them dealing with an irregular sub-topology of the original network. The result of our comparison is that, although they were defined ...

This paper proposes a parallel algorithm for contour tracking of binary pictures. Given an object contour composed by O(N ) pixels, our algorithm computes in constant time the next layer of the contour of that object, using the weakest parallel model, i.e., an Exclusive Read Exclusive Write (EREW) Parallel Random Acces Machine (PRAM). As an application of the technique we show a work-optimal parallel thinning algorithm for binary pictures, based on Pavlidis' characterisation of a skeleton. Our algorithm improves on previous solutions by producing a list of coordinates corresponding to the skeleton contour in O(N ) time with O(N ) processors in an EREW PRAM, where N is the width of the picture. Keywords: Pattern recognition, Skeleton, Parallel complexity, PRAM R'esum'e Nous proposons un algorithme parall`ele original de trac'e de contour dans une image binaire. La dimension de l'image 'etant N \Theta N , l'ensemble des pixels des contours est de taille O(N ), notre algorith...