Novel types of analogic CNN algorithms for recognizing bank-notes

Abstract

Novel types of analogic algorithms, using spatio-temporal CNN (cellular nonlinear/neural networks) operations are introduced. These algorithms make complex decisions in images without reading out the CNN chip. This makes them extremely time, area, and power effective. Two crucial effects are emphasized: diffusion type templates are applied during a finite time interval and local logic operates within well defined parts (patches) in the image plane. Hence, a new type of pattern recognition algorithm is introduced. The technique is demonstrated on an example. In our example we are dealing with an actual problem: how to avoid the counterfeiting on color copiers.<>