Name
Abstract | ||
|---|---|---|
This paper present a cellular automaton (CA) based diffusion model and its application in the edge detection of images. The CA-based diffusion model consists of a regular lattice of cells with local state. These cells interact with their neighbors subject to a uniform rule which governs all cells. By setting the initial condition as an image, the diffusion model can be used as an alternative tool for diffusion equation in image processing. Experimental results showed that the CA-based diffusion model has a steady and convergent dynamical behavior and a better performance than the diffusion equation. This model can detects the image edge more accurately and suppress the noise much better than the classical edge detectors, such as LoG, Laplace, Canny and Sobel operators. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1007/978-3-540-85984-0_112 | ICIC (2) |
Keywords | Field | DocType |
classical edge detector,ca-based diffusion model,edge detection,image edge,diffusion equation,sobel operator,cells interact,image processing,cellular automatic method,diffusion model,better performance,initial condition,cellular automaton | Anisotropic diffusion,Cellular automaton,Edge detection,Computer science,Image processing,Sobel operator,Artificial intelligence,Discrete mathematics,Pattern recognition,Algorithm,Initial value problem,Diffusion (business),Diffusion equation | Conference |
Volume | ISSN | Citations |
5227 | 0302-9743 | 1 |
PageRank | References | Authors |
0.36 | 3 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yu Chen | 1 | 391 | 75.79 |
| Zhuang-zhi Yan | 2 | 14 | 8.28 |