Negentropic Planar Symmetry Detector
This addresses the need for high-precision symmetry detection in applications like quality control, though it appears incremental as it builds on existing information theory concepts.
The paper tackled the problem of detecting reflectional and rotational symmetries in greyscale images by reducing it to detecting point-symmetry and periodicity in one-dimensional negentropy functions, resulting in a method that demonstrated superior performance in experimental verification.
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.