Title :
Image Segmentation by Co-existing Strange Attractor Networks
Author :
Yunzhong Song ; Yanyan Li
Author_Institution :
Complex Network Lab., Henan Polytech. Univ., Jiaozuo, China
Abstract :
Based on the framework of concurrent synchronization of dynamical systems, the Newton-Leipnik (NL) chaotic oscillator network with co-existing strange attractors, are proposed to solve image segmentation. The N-L oscillators whose underlying visual stimulative atoms belong to the same visual group synchronize more quickly compared with F-N neural oscillators, and the segmentation obtained by N-L oscillators seems more subtle using the same number of classes. The simulation has shown that the N-L co-existing strange attractor network achieves promising results on image segmentation.
Keywords :
Newton method; image segmentation; F-N neural oscillators; Newton-Leipnik chaotic oscillator network; concurrent synchronization; dynamical systems; image segmentation; strange attractor networks; visual group; visual stimulative atoms; Chaos; Couplings; Image segmentation; Oscillators; Physics; Synchronization; Visualization; Newton-Leipnik system; image segmentation; neural oscillator; strange attractor;
Conference_Titel :
Chaos-Fractals Theories and Applications (IWCFTA), 2011 Fourth International Workshop on
Conference_Location :
Hangzhou
Print_ISBN :
978-1-4577-1798-7
DOI :
10.1109/IWCFTA.2011.91