Fast pattern recognition using gradient-descent search in an image pyramid

A new technique for fast pattern recognition using normalized grey-scale correlation (NGC) is described. While NGC has traditionally been slow due to computational intensity issues, the introduction of both a pyramid structure and a local estimate of the correlation surface gradient allows for recognition in 10-50 ms using modest microcomputer hardware. The algorithm is designed to analyze the target off-line prior to starting the search. Issues surrounding determining an appropriate depth for the pyramid representation and performing sub-pixel localization of the target instance are discussed. The speed and robustness of the method makes it attractive for industrial applications.