Fast and numerically stable circle fit
This addresses the need for a fast and stable circle fit in computational geometry and related fields, representing an incremental improvement over existing methods.
The paper tackles the problem of fitting circles by developing a new algorithm that achieves machine precision accuracy, avoids divergence, and is numerically stable even for arbitrarily large circles, with convergence in less than 10 iterations on average.
We develop a new algorithm for fitting circles that does not have drawbacks commonly found in existing circle fits. Our fit achieves ultimate accuracy (to machine precision), avoids divergence, and is numerically stable even when fitting circles get arbitrary large. Lastly, our algorithm takes less than 10 iterations to converge, on average.