Parallel algorithm of image recognition based on cellular neural network
Stirenko S.G., Mitin S.V.
In this paper a simple but effective approach for parallelization of cellular neural networks for image processing is developed. Digital gray-scale images were used to evaluate the program. The approach uses the SPMD model and is based on the structural data parallel approach. The process of parallelizing the algorithm employs HPF to generate an MPI-based program and the performance behavior was analyzed on two different cluster architectures.