Automatic corner matching in highly distorted images of Zhang’s calibration pattern

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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.

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Alemán-Flores, M., Alvarez, L., Gomez, L., & Santana-Cedrés, D. (2014). Automatic corner matching in highly distorted images of Zhang’s calibration pattern. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8827, pp. 754–761). Springer Verlag. https://doi.org/10.1007/978-3-319-12568-8_91

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