  In this paper we observe that information theoretical concepts are valuable
tools for extracting information from images and, in particular, information on
image symmetries. It is shown that the problem of detecting reflectional and
rotational symmetries in a two-dimensional image can be reduced to the problem
of detecting point-symmetry and periodicity in one-dimensional negentropy
functions. Based on these findings a detector of reflectional and rotational
global symmetries in greyscale images is constructed. We discuss the importance
of high precision in symmetry detection in applications arising from quality
control and illustrate how the proposed method satisfies this requirement.
Finally, a superior performance of our method to other existing methods,
demonstrated by the results of a rigorous experimental verification, is an
indication that our approach rooted in information theory is a promising
direction in a development of a robust and widely applicable symmetry detector.
