Pattern extraction and recognition for noisy images using the three-layered BP model

The authors present a novel pattern recognition architecture using three-layered backpropagation (BP) models. The proposed architecture consists mainly of the following two completely separate functions: extraction of a target pattern and recognition of the extracted pattern. It is possible that the proposed architecture detects where and what the target pattern is. In order to realize these functions, the following networks are introduced: filtering network, position network, size network, frame-working network, and categorizing networks. Results of handwritten-letter recognition experiments show that the proposed architecture has the ability to recognize a deformed target pattern in an original image with much noise, especially lumped noises. >