| Abstract / Kurzbeschreibung: |
The calibration of cameras is a crucial step in machine vision and usually
relies on an accurate detection and localization of calibration patterns in
images. Therefore, checkerboards are often used, allowing precise subpixel
estimation of their corners. However, noise in localization generates a
proportional noise in the derived model parameters. Therefore, it is important
that the localization has a certain robustness against image noise. This is even
more important for deteriorated imaging conditions strongly affecting
subpixel detectors.
This paper presents a new checkerboard corner detector based on a localized
Radon transform implemented by large box filters making it robust to low
contrast, image noise, and blur while maintaining high subpixel
accuracy. |
