FITTING A CONIC A-SPLINE TO CONTOUR IMAGE DATA

Abstract

In this paper an algorithm for constructing contours from image data by means of a G1 conic A-spline is presented. A conic A-spline is a piecewise smooth chain of connected real quadratic algebraic curves meeting G1 at the junction points. Once the contour of the image data has been extracted, the algorithm computes the breakpoints of the conic A-spline, i.e the junction points for the conic curves make up the curve. Inflection points are also added to the set of junction points of the A-spline. Tangent lines at the
junction points are computed using a weighted least square linear fit instead of the classical divided difference techniques. The conic A-spline interpolates the junction points along with the tangent directions and least-squares approximates the given data between junction points. We discuss and compare our experience with the approaches reported in the recent literature. Additionally, we propose some improvements