Breakpoint detection using covariance propagation

This paper presents a novel statistical approach for detecting breakpoints from chain encoded digital arcs. An are point is declared as a breakpoint if the estimated orientations of the two fitted lines of the two are segments immediately to the right and left of the are point are significantly statistically different. The major contributions of this research include developing a method for analytically estimating the covariance matrix of the fitted line parameters and proposing a perturbation model to characterize the perturbation associated with each are point.