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Fitting parabolas in noisy images

Authors: García Escudero, Luis Ángel; Mayo Iscar, Agustín; Sánchez Gutiérrez, Clara I.;

Fitting parabolas in noisy images

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 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.

Countries
Netherlands, Spain
Keywords

retinography, Procrustes analysis, Radboudumc 12: Sensory disorders DCMN: Donders Center for Medical Neuroscience, parabola fitting, Medical Imaging - Radboud University Medical Center, Estadística, robustez, parabolas retinografías, robustness, Computational methods for problems pertaining to statistics, Computing methodologies for image processing

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    selected citations
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    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    6
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
6
Top 10%
Average
Average
Green
hybrid