Composite wavelet based morphological correlation for continuous-scale-invariant pattern recognition

A composite nonlinear correlation is proposed to perform invariant recognition for the input image with continuous-scale distortions. The proposed correlation can be considered as a summation of many composite wavelet matched filters. Every matched filter consists of a linear combination of binary slices that are generated from threshold decomposition of the training images, and an adaptive wavelet filter. The adaptive wavelet is optimized to produce the sparse image features. Computer simulations are carried out to prove the scale-invariance and noise robustness of the new scheme.