A three-dimensional (3D) pattern recognition technique using the concept of fringe-adjusted joint transform correlation is proposed in this thesis. The proposed technique yields better correlation discrimination ability compared to alternate 3D classical joint transform correlation by producing sharper and stronger correlation peak intensity. Simulation results verify the effectiveness of the proposed technique.
