A hybrid optical/digital correlator filter synthesis architecture for distortion-invariant pattern recognition and scene analysis is described. Distortion-invariant correlation filter synthetic discriminant function design is reviewed. Computer generated hologram filter synthesis concepts are then reviewed. Emphasis is given to the optical laboratory realization of the filters for such systems. The issues addressed include: the number of training images, selection of the shift parameter in filter design, the ability of the system to recognize rotated (non-training) images, what the largest false class peak correlation (anywhere, not just at the correlation peak point) is, and solutions to the non-zero optical transmittance of input and filter films. Laboratory results for all major points are provided.