Class-associative color pattern recognition using a shifted phase-encoded joint transform correlation

A new shifted phase-encoded fringe-adjusted joint transform correlation (SPJTC) technique is proposed for class-associative color pattern recognition. In this technique, the joint color image containing the class member images and unknown input scene images is split into three fundamental color components—red, green, and blue—which are then processed through three different channels using the SPJTC technique to obtain individual joint power spectra (JPS). For correlation performance improvement, a new class-associative color fringe-adjusted filter (CCFAF) has been proposed. The combined JPSs obtained by fusing all of the individual joint power spectra are then multiplied by the CCFAF transfer function. The proposed scheme provides a single correlation peak per target with excellent correlation discrimination for both noise-free and noisy conditions. Simulation results are provided to verify the effectiveness of the proposed technique.