Abstract
Nonlinear morphological correlation provides some better performances in pattern recognition than linear correlation. However, it requires considerable amount of computational effort to obtain the final result. An adaptive threshold decomposition technique is proposed to reduce the computation and increase the processing speed. Computer simulation shows that the proposed method yields similar results to the original morphological correlation but with much less computational effort. A visual-area-coding technique is proposed to implement the morphological correlation optically in a single step. This alternative optical implementation provides several advantages over the optical morphological correlation schemes.