Simulating optical pattern recognition algorithms for object tracking based on nonlinear models and subtraction of frames

Abstract

We have proposed and discussed optical pattern recognition algorithms for object tracking based on nonlinear equivalence models and subtraction of frames. Experimental results of suggested algorithms in Mathcad and LabVIEW are shown. Application of equivalent functions and difference of frames gives good results for recognition and tracking moving objects