Real-time Image Processing by Cellular Neural Network Using Reaction-Diffusion Model

In this paper we propose two architectures of cellular neural network (CNN) for edge detection and segmentation of noisy image based on FitzHugh-Nagumo reaction-diffusion equation. These networks give better results compare to other methods and are capable to real-time applications due to parallel processing nature of the CNN. The mathematical description and nonlinear phenomena analysis of the FitzHugh-Nagumo reaction-diffusion equation are given to show its operating principle in edge detection and segmentation. The method to define the templates of these CNNs is presented and we also give some Matlab simulations to demonstrate the effectiveness of the proposed method.