DISTANCE APPROXIMATIONS FOR RASTERIZING IMPLICIT CURVES

In this article we present new algorithms for rasterizing implicit curves, i.e., curves represented as level sets of functions of two variables. Considering the pixels as square regions of the plane, a ''correct'' algorithm should paint those pixels whose centers lie at less than half the desired line width from the curve. A straightforward implementation, scanning the display array evaluating the Euclidean distance from the center of each pixel to the curve, is impractical, and a standard quad-tree-like recursive subdivision scheme is used instead. Then we attack the problem of testing whether or not the Euclidean distance from a point to an implicit curve is less than a given threshold. For the most general case, when the implicit function is only required to have continuous first-order derivatives, we show how to reformulate the test as an unconstrained global root-finding problem in a circular domain. For implicit functions with continuous derivatives up to order k we introduce an approximate distance of order k. The approximate distance of order k from a point to an implicit curve is asymptotically equivalent to the Euclidean distance and provides a sufficient test for a polynomial of degree k not to have roots inside a circle. This is the main contribution of the article. By replacing the Euclidean distance test with one of these approximate distance tests, we obtain a practical rendering algorithm, proven to be correct for algebraic curves. To speed up the computation we also introduce heuristics, which used in conjunction with low-order approximate distances almost always produce equivalent results. The behavior of the algorithms is analyzed, both near regular and singular points, and several possible extensions and applications are discussed.