In this paper a method for symmetry axis detection in binary images is presented. The method exploits the nonlinear dynamic behavior of Cellular Neural Networks (CNNs), in particular the propagation of bipolar waves. The image is represented in polar form, transforming the symmetry with respect to an arbitrarily oriented axis in a vertical symmetry: the position of the vertical axis corresponds to the angle of the original symmetry axis. The parallel CNN architecture is useful to speed up the computation, because of the high computational cost of the task. The proposed algorithm is tested on a real image with good results.
Costantini, G., Casali, D. (2007). Detection of symmetry axis by a CNN-based algorithm. In Proceedings of the 11th WSEAS International Conference on Circuits, Vol 1 - CIRCUITS THEORY AND APPLICATIONS (pp.46-49). ATHENS : WORLD SCIENTIFIC AND ENGINEERING ACAD AND SOC.
Detection of symmetry axis by a CNN-based algorithm
COSTANTINI, GIOVANNI;
2007-01-01
Abstract
In this paper a method for symmetry axis detection in binary images is presented. The method exploits the nonlinear dynamic behavior of Cellular Neural Networks (CNNs), in particular the propagation of bipolar waves. The image is represented in polar form, transforming the symmetry with respect to an arbitrarily oriented axis in a vertical symmetry: the position of the vertical axis corresponds to the angle of the original symmetry axis. The parallel CNN architecture is useful to speed up the computation, because of the high computational cost of the task. The proposed algorithm is tested on a real image with good results.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
