Robust Localisation of Circular Objects
Fabian Timm, Thomas Martinetz, and Erhardt Barth
The detection of circular objects (annuli or circles) is a fundamental
problem in pattern recognition. In the case of eye tracking, for
example, the centre of the pupil has to be determined accurately and in
real time. Also, in industrial applications such as automatic
inspection of manufactured components, often circular objects have to be
We created images of 150 x 150 containing an annulus or a circle with
a random centre (near to the image centre) and a fixed size. The grey
values of the annulus/circle were uniformly distributed within the
interval [40,70] and the grey values of the background were uniformly
distributed within [50,80]. Thus, the images contained white noise and
the image contrast was very low. We further added multiplicative noise
(speckle) and applied a motion blur to the images with white noise. For
each object and each type of noise we created 100 images, which gives in
total a dataset of 600 images.
The dataset can be downloaded here.
If you use this dataset for any publication, please refer to this: F. Timm, T. Martinetz, E. Barth. Robust Localisation of Circular Objects.