Optimization of Point Selection on Digital Ink Curves

Digital ink curves are typically represented as series of points sampled at certain time intervals. We are interested in the problem of how to select a minimal subset of sample points to approximate a digital ink curve within a given error bound. We present an algorithm to find an approximation with a specified number of points and providing the minimum cumulative error. Alternatively, it may be used to select the minimum number of points required to satisfy an error bound. The method uses dynamic programming and has a cost linear in the number of points.