Optical pattern recognition in motion acquired scenes using a binary joint transform correlation

The problem of detecting patterns in moved scenes is analysed. The correlation when the input scene presents a relative motion with respect to the recording system image is studied analytically and an original method for detecting patterns by means of a binary joint transform correlator is presented. The method is based on the compensation of the sign errors introduced in the joint power spectrum by the transfer function of the degradation. Two alternatives to determine the sign of the transfer function are demonstrated: the first is based on an algorithm to extract information from the Fourier spectrum of the blurred image and the second method determines the sign errors by post-processing the correlation. Digital simulations and optical results are provided.