Fast diffraction-pattern matching for object detection and recognition in digital holograms

A digital hologram is a 2-D recording of the diffraction fringes created by 3-D objects under coherent lighting. These fringes encode the shape and 3-D location information of the objects. By simulating re-lighting of the hologram, the 3-D wave field can be reconstructed and a volumetric image of the objects recovered. Rather than performing object detection and identification in this reconstructed volume, we consider direct recognition of diffraction-patterns in in-line holograms and show that it leads to superior performance. The huge variability of diffraction patterns with object shape and 3-D location makes diffraction-pattern matching computationally expensive. We suggest the use of a dimensionality reduction technique to circumvent this limitation and show good detection and recognition performance both on simulated and experimental holograms.