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Fitting parabolas in noisy images

Author

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  • García-Escudero, Luis A.
  • Mayo-Iscar, Agustín
  • Sánchez-Gutiérrez, Clara I.

Abstract

A novel approach to fitting parabolas to scattered data is introduced by putting special emphasis on the robustness of the approach. The robust fit is achieved by not taking into account a proportion α of the “most outlying” observations, allowing the procedure to trim them off. The most outlying observations are self-determined by the data. Procrustes analysis techniques and a particular type of “concentration” steps are the keystone of the proposed methodology. An application to a retinographic study is also presented.

Suggested Citation

  • García-Escudero, Luis A. & Mayo-Iscar, Agustín & Sánchez-Gutiérrez, Clara I., 2017. "Fitting parabolas in noisy images," Computational Statistics & Data Analysis, Elsevier, vol. 112(C), pages 80-87.
    • Handle: RePEc:eee:csdana:v:112:y:2017:i:c:p:80-87
    DOI: 10.1016/j.csda.2017.03.008
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    Cited by:

    1. Greco, Luca & Pacillo, Simona & Maresca, Piera, 2023. "An impartial trimming algorithm for robust circle fitting," Computational Statistics & Data Analysis, Elsevier, vol. 181(C).

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