A network of coupled chaotic maps for adaptive multi-scale image segmentation.
In this paper, a network of coupled chaotic maps for multi-scale image segmentation is proposed. Time evolutions of chaotic maps that correspond to a pixel cluster are synchronized with one another, while this synchronized evolution is desynchronized with respect to time evolution of chaotic maps corresponding to other pixel clusters in the same image. The number of pixel clusters is previously unknown and the adaptive pixel moving technique introduced in the model makes it robust enough to classify ambiguous pixels.
Zhao
Liang
L
Department of Computer Science and Statistics, University of São Paulo, Av. do Trabalhador São-Carlense, 400, Caixa Postal: 668, São Carlos, SP, 13560-970, Brazil. zhao,furukawa,andre@icmc.usp.br
Furukawa
Rogerio A
RA
Carvalho
Andre C P L F
AC
D000818:Animals; D016000:Cluster Analysis; D006801:Humans; D007091:Image Processing, Computer-Assisted; D007255:Information Services; D008377:Maps as Topic; D009474:Neurons; D017711:Nonlinear Dynamics; D011897:Random Allocation; D013223:Statistics as Topic; D013997:Time Factors