A what-and-where neural network for invariant image preprocessing

Abstract

A feedforward neural networks for invariant image preprocessing is proposed that represents the position, orientation, and size of an image figure (where it is) in a multiplexed spatial map. This map is used to generate an invariant representation of the figure that is insensitive to position, orientation, and size for purposes of pattern recognition (what it is). Image recognition is based upon the output from the what channel. A multiscale array of oriented filters, followed by competition between orientations and scales, is used to define the where filter.<>