Identificador persistente para citar o vincular este elemento: http://hdl.handle.net/10553/45746
Título: Wide-angle lens distortion correction using division models
Autores/as: Alemán-Flores, Miguel 
Alvarez, Luis 
Gomez, Luis 
Santana-Cedreś, Daniel 
Clasificación UNESCO: 220990 Tratamiento digital. Imágenes
120601 Construcción de algoritmos
120602 Ecuaciones diferenciales
120326 Simulación
Fecha de publicación: 2013
Proyectos: Modelización Matemática de Los Procesos de Calibración de Cámaras de Video. 
Publicación seriada: Lecture Notes in Computer Science 
Conferencia: 18th Iberoamerican Congress on Pattern Recognition, CIARP 2013 
Resumen: In this paper we propose a new method to automatically correct wide-angle lens distortion from the distorted lines generated by the projection on the image of 3D straight lines. We have to deal with two major problems: on the one hand, wide-angle lenses produce a strong distortion, which makes the detection of distorted lines a particularly difficult task. On the other hand, the usual single parameter polynomial lens distortion models is not able to manage such a strong distortion. We propose an extension of the Hough transform by adding a distortion parameter to detect the distorted lines, and division lens distortion models to manage wide-angle lens distortion. We present some experiments on synthetic and real images to show the ability of the proposed approach to automatically correct this type of distortion. A comparison with a state-of-the-art method is also included to show the benefits of our method.
URI: http://hdl.handle.net/10553/45746
ISBN: 978-3-642-41821-1
ISSN: 0302-9743
DOI: 10.1007/978-3-642-41822-8_52
Fuente: Ruiz-Shulcloper J., Sanniti di Baja G. (eds) Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications. CIARP 2013. Lecture Notes in Computer Science, vol 8258. Springer, Berlin, Heidelberg
Colección:Actas de congresos
miniatura
pdf
Adobe PDF (998,79 kB)
Vista completa

Citas SCOPUSTM   

8
actualizado el 24-mar-2024

Visitas

66
actualizado el 17-sep-2022

Google ScholarTM

Verifica

Altmetric


Comparte



Exporta metadatos



Los elementos en ULPGC accedaCRIS están protegidos por derechos de autor con todos los derechos reservados, a menos que se indique lo contrario.