Abstract
In this paper we propose a simple neural network architecture for
invariant image recognition. The proposed neural network architecture
contains three specialized modules. The neurons from the first module
are connected in a cellular neural network structure, which is
responsible for image processing: edge detection and segmentation. The
second module is a feed forward neural network for invariant feature
extraction from the sensorial layer: computation of the pair
distribution function and bond angle distribution function. The third
module is responsible for image classification. An application to the
face recognition problem is also presented.