Gray Level Image Edge Detection Using a Hybrid Model of Cellular Learning Automata and Stochastic Cellular Automata


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.

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Vatani, N. and Enayatifar, R. (2015) Gray Level Image Edge Detection Using a Hybrid Model of Cellular Learning Automata and Stochastic Cellular Automata. Open Access Library Journal, 2, 1-8. doi: 10.4236/oalib.1101203.

Conflicts of Interest

The authors declare no conflicts of interest.


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