A complex texture classification algorithm based on Gabor-type filtering cellular neural networks and self-organized fuzzy inference neural networks

In this paper, a bio-inspired complex texture classification algorithm has been introduced. This algorithm included two neural networks; one is the Gabor-type filtering cellular neural network which is used to simulate the human retina, the other is the self-organized fuzzy inference neural network which is used to simulate the brain. Both the neural networks can be considered as feedforward neural networks. Thus, we can say that the whole system which has been introduced in this paper is also a feedforward system and it contains the ability for parallel processing.