OPTIMAL CONIC FITTING AND RELIABILITY EVALUATION

Introducing a mathematical model of image noise, we formalize the prob lem of fitting a conic to point data as statistical estimation. It is shown that The reliability of the fitted conic can be evaluated quanti tatively in the form of the covariance tensor. We present a numerical scheme called renormalization for computing an optimal fit and at the same time evaluating its reliability, We also present a scheme for vis ualizing the reliability of the fit by means of the primary deviation pair. Our method is illustrated by showing simulations and real-image examples.