We present a two-layer neural network for processing of three-dimensional (3D) images that are obtained by digital holography. The network is trained with a real 3D object to compute the weights of the layers. Experiments are presented to illustrate the system performance. The system is designed to detect a 3D object in the presence of various distortions. As an example, experiments are presented to illustrate how the system is able to recognize a 3D object with 360° out-of-plane rotation.
© 2001 Optical Society of America
(090.1760) Holography : Computer holography
(100.5760) Image processing : Rotation-invariant pattern recognition
(100.6740) Image processing : Synthetic discrimination functions
(100.6890) Image processing : Three-dimensional image processing
Yann Frauel and Bahram Javidi, "Neural network for three-dimensional object recognition based on digital holography," Opt. Lett. 26, 1478-1480 (2001)