TITLE:
Gray Level Image Edge Detection Using a Hybrid Model of Cellular Learning Automata and Stochastic Cellular Automata
AUTHORS:
Nasim Vatani, Rasul Enayatifar
KEYWORDS:
Cellular Learning Automata, Stochastic Cellular Automata, Edge Detection, Image Processing, Statistic Feature
JOURNAL NAME:
Open Access Library Journal,
Vol.2 No.1,
January
23,
2015
ABSTRACT: 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.