Improved direct fitting algorithm for elliptic parameters

For the ellipse fitting problem often encounter in visual measurement, this paper proposes a method combining algebraic distance fitting method based on least squares and characteristic root method for ellipse fitting. Firstly, the improved hierarchical agglomerative clustering is used to denoise the data. Then the algebraic distance fitting method based on least squares is used to calculate the initial iteration value of the parameters in the characteristic root method. Finally, the Gauss-Newton iteration method is used to solve the elliptic parameters. This algorithm is used to detect the out-of-roundness of the optical fiber and compare the test results with the high-precision optical fiber tester FGM-502. The results prove the validity and accuracy of the ellipse fitting algorithm studied in this paper and show that the algorithm studied in this paper meets the requirements of actual ellipse fitting measurement.