Title :
Fast pattern recognition using gradient-descent search in an image pyramid
Author :
MacLean, James ; Tsotsos, John
Author_Institution :
Dept. of Comput. Sci., Toronto Univ., Ont., Canada
Abstract :
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
Keywords :
computational complexity; gradient methods; image recognition; image representation; microcomputer applications; search problems; 10 to 50 ms; NGC; computational intensity; correlation surface gradient; fast pattern recognition; gradient-descent search; image pyramid; industrial applications; normalized grey-scale correlation; pyramid representation depth; sub-pixel localization; target analysis; target instance; Algorithm design and analysis; Cameras; Computer science; Hardware; Image recognition; Manufacturing industries; Microcomputers; Pattern matching; Pattern recognition; Robustness;
Conference_Titel :
Pattern Recognition, 2000. Proceedings. 15th International Conference on
Conference_Location :
Barcelona
Print_ISBN :
0-7695-0750-6
DOI :
10.1109/ICPR.2000.906213