49 research outputs found
Traffic Analysis in Random Delaunay Tessellations and Other Graphs
In this work we study the degree distribution, the maximum vertex and edge
flow in non-uniform random Delaunay triangulations when geodesic routing is
used. We also investigate the vertex and edge flow in Erd\"os-Renyi random
graphs, geometric random graphs, expanders and random -regular graphs.
Moreover we show that adding a random matching to the original graph can
considerably reduced the maximum vertex flow.Comment: Submitted to the Journal of Discrete Computational Geometr
Generating Automatically-Tuned Bitmaps from Outlines
Consider the problem of generating bitmaps from character shapes given as outlines. The obvious scan-conversion process does not produce acceptable results unless important features such as stem widths are carefully controlled during the scan-conversion process. This paper describes a method for automatically extracting the necessary feature information and generating high quality bitmaps without resorting to hand editing. Almost all of the work is done in a preprocessing step, the result of which is an intermediate form that can be quickly converted into bitmaps once the font size and device resolution are known. A heuristically defined system of linear equations describes how the ideal outlines should be distorted in order to produce the best possible results when scan converted in a straight-forward manner. The Lov'asz basis reduction algorithm then reduces the system of equations to a form that makes it easy to find an approximate solution subject to the constraint that some variab..
Rasterization of Nonparametric Curves
We examine a class of algorithms for rasterizing algebraic curves based on an implicit form that can be evaluated cheaply in integer arithmetic using finite differences. These algorithms run fast and produce "optimal" digital output, where previously known algorithms have had serious limitations. We extend previous work on conic sections to the cubic and higher order curves, and we solve an important undersampling problem