LAWS@IU.AI.SRI.COM (Ken Laws) (04/21/88)
Thanks for the comments you tacked onto my comp.ai.digest query about holographic pattern recognition. > ... Field target-recognition systems are likely to use holograms or > acoustic-wave devices because they are faster than digital techniques > and more robust than complex lens systems ... Holographic systems > storing dozens of different views of tanks and aircraft have been > demonstrated. Can you point me to any reference on this stuff, or is it all classified? Raymond Lister Most of it isn't classified, but it's so widely distributed that I hardly know where to begin looking. We're talking about entire fields of 2-D matched filtering, optical target queueing, correlation matching, character recognition, etc. I remember seeing conference papers on these tank/aircraft recognizers, but would need about a day to track them down. The SPIE and CVPR conferences would be good places to start. You might like the March '87 Scientific American article by Abu-Mostafa and Psaltis on Optical Neural Computers, although they emphasize associative memory rather than recognition. (Recognition simply taps a different plane in the optical system.) David Casasent at CMU is active in this field. I have one of his papers that's relevant: Optical Word Recognition: Case Study in Coherent Optical Pattern Recognition, SPIE Optical Engineering, Vol. 19, No. 5, Sep/Oct 1980, pp. 716-721. Another paper that comes to hand, although not a great illustration, is Mendelsohn, Wohlers, and Leib, Digital Analysis of the Effects of Terrain Clutter on the Performance of Matched Filters for Target Identification and Location, SPIE Vol. 186, Digital Processing of Aerial Images, 1979, pp. 190-196. Some early papers on correlation matching and Fourier signatures can be found in Computer Methods in Image Analysis, a book of reprints edited by Aggarwal, Duda, and Rosenfeld. Two examples are Horwitz and Shelton, Pattern Recognition using Autocorrelation, and Lendaris and Stanley, Diffraction-Pattern Sampling for Automatic Pattern Recognition. For somewhat more recent work see Agrawala's book of reprints, Machine Recognition of Patterns. Examples are Preston's A Comparison of Analog and Digital Techniques for Pattern Recognition, and Holt's Comparative Religion in Character Recognition Machines. I think I should emphasis that these correlation-based matching methods are rather fragile. Casasent has done a lot of work on recognizing patterns that may be rotated or scaled, but most of these techniques require exact matches of standard, isolated characters against uniform backgrounds. They will not recognize handwritten characters, for instance. -- Ken