Neural network for three-dimensional object recognition based on digital holography
Optics Letters, Vol. 26, Issue 19, pp. 1478-1480 (2001)
http://dx.doi.org/10.1364/OL.26.001478
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Abstract
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
[Optical Society of America ]
OCIS Codes
(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
Citation
Yann Frauel and Bahram Javidi, "Neural network for three-dimensional object recognition based on digital holography," Opt. Lett. 26, 1478-1480 (2001)
http://www.opticsinfobase.org/ol/abstract.cfm?URI=ol-26-19-1478
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