Geometrical analysis of polynomial lens distortion models

Ronda Prieto, José Ignacio and Valdés Morales, Antonio (2019). Geometrical analysis of polynomial lens distortion models. "Journal of Mathematical Imaging adn Vision", v. 61 (n. 3); pp. 252-268. ISSN 0924-9907.


Title: Geometrical analysis of polynomial lens distortion models
  • Ronda Prieto, José Ignacio
  • Valdés Morales, Antonio
Item Type: Article
Título de Revista/Publicación: Journal of Mathematical Imaging adn Vision
Date: 14 July 2019
ISSN: 0924-9907
Volume: 61
Freetext Keywords: Lens distortion; Camera calibration; Polynomial model
Faculty: E.T.S.I. Telecomunicación (UPM)
Department: Señales, Sistemas y Radiocomunicaciones
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Polynomial functions are a usual choice to model the nonlinearity of lenses. Typically, these models are obtained through physical analysis of the lens system or on purely empirical grounds. The aim of this work is to facilitate an alternative approach to the selection or design of these models based on establishing a priori the desired geometrical properties of the distortion functions. With this purpose we obtain all the possible isotropic linear models and also those that are formed by functions with symmetry with respect to some axis. In this way, the classical models (decentering, thin prism distortion) are found to be particular instances of the family of models found by geometric considerations. These results allow to find generalizations of the most usually employed models while preserving the desired geometrical properties. Our results also provide a better understanding of the geometric properties of the models employed in the most usual computer vision software libraries.

Funding Projects

Government of SpainTEC2016-75981IVMEUnspecifiedUnspecified
Government of SpainTIN2016-75982-C2-2-RHEIMDAL-UPMUnspecifiedDetección semántica multisensorial de situaciones anómalas en entornos sin restricciones

More information

Item ID: 64244
DC Identifier:
OAI Identifier:
DOI: 10.1007/s10851-018-0833-x
Official URL:
Deposited by: Memoria Investigacion
Deposited on: 12 Dec 2020 10:57
Last Modified: 12 Dec 2020 10:57
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