DocumentCode :
1929824
Title :
Image segmentation using an emergent complex system: Cellular automata
Author :
Safia, Djemame ; Chawki, Batouche Mohamed
Author_Institution :
Comput. Sci. Dept., Ferhat Abbes Univ., Sétif, Algeria
fYear :
2011
fDate :
9-11 May 2011
Firstpage :
207
Lastpage :
210
Abstract :
Cellular automata are simple models of computation which exhibit fascinatingly complex behavior. They have captured the attention of several generations of researchers, leading to an extensive body of work. The emphasis is mainly on topics closer to computer science and mathematics rather than physics, biology or other applications. Many related works were interested in cellular automata capacities in image processing, but all of them were confronted with the problem of increase of rules number towards the number of cells states. In this paper, we propose an original solution to avoid this problem, the objective is a segmentation by edge detection, applied to binary images, grey level images and real images. Comparisons are made with standard edge detector (Canny) and algorithms based on cellular automata. Obtained results are encouraging.
Keywords :
cellular automata; edge detection; image segmentation; binary images; cellular automata; edge detection; edge detector; emergent complex system; grey level images; image segmentation; real images; Automata; Filtering; Image edge detection; Image segmentation; Pixel; Smoothing methods;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Systems, Signal Processing and their Applications (WOSSPA), 2011 7th International Workshop on
Conference_Location :
Tipaza
Print_ISBN :
978-1-4577-0689-9
Type :
conf
DOI :
10.1109/WOSSPA.2011.5931453
Filename :
5931453
Link To Document :
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