Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/45745
Title: Automatic corner matching in highly distorted images of Zhang’s calibration pattern
Authors: Alemán-Flores, Miguel 
Alvarez, Luis 
Gomez, Luis 
Santana-Cedrés, Daniel 
UNESCO Clasification: 220990 Tratamiento digital. Imágenes
120601 Construcción de algoritmos
120602 Ecuaciones diferenciales
120326 Simulación
Keywords: Camera calibration
Lens distortion
Zhang’s method
Issue Date: 2014
Publisher: Springer
Project: Modelización Matemática de Los Procesos de Calibración de Cámaras de Video. 
Journal: Lecture Notes in Computer Science 
Conference: 19th Iberoamerican Congress on Pattern Recognition (CIARP 2014) 
Abstract: Zhang’s method is a widely used technique for camera calibration from different views of a planar calibration pattern. This pattern contains a set of squares arranged in a certain configuration. In order to calibrate the camera, the corners of the squares in the images must be matched with those in the reference model. When the images show a strong lens distortion, the usual methods to compute the corner matching fail because the corners are shifted from their expected positions. We propose a new method which automatically estimates such corner matching taking into account the lens distortion. The method is based on an automatic algorithm for lens distortion correction which allows estimating the distorted lines passing through the edges of the squares. We present some experiments to illustrate the performance of the proposed method, as well as a comparison with the usual technique proposed in a Matlab toolbox.
URI: http://hdl.handle.net/10553/45745
ISBN: 978-3-319-12567-1
ISSN: 0302-9743
DOI: 10.1007/978-3-319-12568-8_91
Source: Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications. CIARP 2014. Lecture Notes in Computer Science, v. 8827 LNCS, p. 754-761
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