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<p>Complex-log conformal mapping is combined with a distributed associative memory to create a system that recognizes objects regardless of changes in rotation or scale. Information recalled from the memorized database is used to classify an object, reconstruct the memorized version of the object, and estimate the magnitude of changes in scale or rotation. The system response is resistant to moderate amounts of noise and occlusion. Several experiments using real gray-scale images are presented to show the feasibility of the approach.</p>
2-D invariant object recognition; computerized pattern recognition; complex log conformal mapping; distributed associative memory; database; system response; gray-scale images; computerised pattern recognition; content-addressable storage

G. Zimmerman and H. Wechsler, "2-D Invariant Object Recognition Using Distributed Associative Memory," in IEEE Transactions on Pattern Analysis & Machine Intelligence, vol. 10, no. , pp. 811-821, 1988.
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