A network of globally coupled chaotic maps for adaptive multi-resolution image segmentation

In this paper, a computational model for image segmentation based on a network of coupled chaotic maps is proposed. Time evolutions of chaotic maps that correspond to a pixel class are synchronized with one another, while this synchronized evolution is desynchronized with respect to time evolution of chaotic maps corresponding to other pixel classes in the same data set. The model presents the following advantages in comparison to conventional pixel classification techniques: 1) the segmentation process is intrinsically parallel; 2) the number of pixel classes can be previous unknown; 3) the model offers a multi-resolution and multi-thresholding segmentation approach; 4) the adaptive pixel moving process makes the model robust to classify ambiguous pixels; and 5) the model obtains good performance and transparent dynamics by utilizing one-dimensional chaotic maps instead of complex neurons as individual elements.

[1]  K. Kaneko.  Clustering, coding, switching, hierarchical ordering, and control in a network of chaotic elements , 1990 .

[2]  H. Fujisaka,et al.  Stability Theory of Synchronized Motion in Coupled-Oscillator Systems , 1983 .

[3]  David G. Stork,et al.  Pattern Classification , 1973 .

[4]  Cerdeira,et al.  Spatiotemporal chaos in rf-driven Josephson junction series arrays. , 1995, Physical review. B, Condensed matter.

[5]  W. Freeman,et al.  How brains make chaos in order to make sense of the world , 1987, Behavioral and Brain Sciences.

[6]  William C. Schieve,et al.  A bifurcation analysis of the four dimensional generalized Hopfield neural network , 1995 .

[7]  Yukio Hayashi,et al.  Oscillatory neural network and learning of continuously transformed patterns , 1994, Neural Networks.

[8]  K. Aihara,et al.  12. Chaotic oscillations and bifurcations in squid giant axons , 1986 .

[9]  Kunihiko Kaneko,et al.  Relevance of dynamic clustering to biological networks , 1993, chao-dyn/9311008.

[10]  Carroll,et al.  Synchronization in chaotic systems. , 1990, Physical review letters.

[11]  Sankar K. Pal,et al.  A review on image segmentation techniques , 1993, Pattern Recognit..

[12]  Liang Zhao,et al.  A network of dynamically coupled chaotic maps for scene segmentation , 2001, IEEE Trans. Neural Networks.

[13]  A. Babloyantz,et al.  Evidence of Chaotic Dynamics of Brain Activity During the Sleep Cycle , 1985 .

[14]  Louis M. Pecora,et al.  Fundamentals of synchronization in chaotic systems, concepts, and applications. , 1997, Chaos.

[15]  John Robinson,et al.  Stability and bifurcations in an associative memory model , 1996, Neural Networks.

[16]  Nizam Omar,et al.  Scene Segmentation of the Chaotic oscillator Network , 2000, Int. J. Bifurc. Chaos.