AN AUTOREGRESSIVE CURVATURE MODEL FOR DESCRIBING CARTOGRAPHIC BOUNDARIES

This paper introduces a new method for representing cartographic bound aries using autoregressive model parameters. An autoregressive model i s presented to model a time series which describes the correlated shap e variations determining the overall shape of the boundary. Such time series are obtained using an appropriate nonperiodic sampling sequence from a curvature function of the boundary. In the nonperiodic samplin g scheme the sampling points are a set of highly informative and signi ficant points. To reduce the sensitivity of curvature to the noise in boundary, the curvature values are estimated at each point using a fil ter with a proper degree of smoothing. The univariate AR model paramet ers are invariant to translation, scale, and rotation of the boundary, and as a consequence this modeling can be used to produce invariant r ecognition and description of cartographic boundaries.