The mathematical model that aims at determining points in an image at
which the image brightness suddenly changes is called edge detection. This
study aims to propose a new
hybrid method for edge detection. This method is based on cellular learning
automata (CLA) and stochastic cellular automata (SCA). In the first part of the
proposed method, statistic features of the input image are hired to have
primary edge detection. In the next step CLA and SCA are employed to amplify
pixels situated on edge and castrate those pixels which are part of the image
background. The simulation results are conducted to prove proposed method
performance and these results suggest that the proposed method is more efficient in finding edges and
outperforms the existing edge detection algorithms.
Cite this paper
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