Scale-invariant 3D face recognition using computer-generated holograms and the Mellin transform

We present a novel method for scale-invariant 3D face recognition by integrating computer-generated holography with the Mellin transform. This approach leverages the scale-invariance property of the Mellin transform to address challenges related to variations in 3D facial sizes during recognition. By applying the Mellin transform to computer-generated holograms and performing correlation between them, which, to the best of our knowledge, is being done for the first time, we have developed a robust recognition framework capable of managing significant scale variations without compromising recognition accuracy. Digital holograms of 3D faces are generated from a face database, and the Mellin transform is employed to enable robust recognition across scale factors ranging from 0.4 to 2.0. Within this range, the method achieves 100% recognition accuracy, as confirmed by both simulation-based and hybrid optical/digital experimental validations. Numerical calculations demonstrate that our method significantly enhances the accuracy and reliability of 3D face recognition, as evidenced by the sharp correlation peaks and higher peak-to-noise ratio (PNR) values than that of using conventional holograms without the Mellin transform. Additionally, the hybrid optical/digital joint transform correlation hardware further validates the method's effectiveness, demonstrating its capability to accurately identify and distinguish 3D faces at various scales. This work provides a promising solution for advanced biometric systems, especially for those which require 3D scale-invariant recognition.