A method of pattern recognition is presented that can recognize image variations such as different perspective views of a three-dimensional object. The general theory allows many different kinds of image variations, such as rotation, scale, perspective, or combinations of these, to be recognized. The method produces a small bank of about 20 filters to be used in a correlator. We call these filters lock-and-tumbler filters. The theory is illustrated on several different kinds of invariant pattern recognition problems. The correlation filters designed for these invariant recognition problems may be modified to reject certain kinds of clutter in an input scene. An example of modifying these filters to achieve rejection of clutter is given. An implementation of the lock-and-tumbler filter method using a high speed digital correlator is then described.
George F. Schils,
"Optical Recognition of 3-D Targets", Proc. SPIE 0960, Real-Time Signal Processing for Industrial Applications, (8 February 1989); doi: 10.1117/12.947792; https://doi.org/10.1117/12.947792