Abstract
A holographic experimental procedure assuming use of quantum states of light is simulated. It uses merely interference-based image storage and nonunitary image retrieval realized by wave function collapse. Successful results of computational view-invariant recognition of object images are presented. As in neural net theory, recognition is selective reconstruction of an image from a database of many concrete images (simultaneously stored in an associative memory) after presentation of a different version of that image. That is, in the first step, we store many high-resolution images of objects into quantum memory (a hologram). In the second step, we present a “nonlearned” noisy image version. We thereby trigger memory-influenced reorganization of the state of the system so that it finally encodes those corrected object images that correspond to the newly presented version. The holographic procedure seems to be implementable with present-day quantum optics.
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From Optika i Spektroskopiya, Vol. 99, No. 2, 2005, pp. 233–238.
Original English Text Copyright © 2005 by Chu Kiong Loo, Peruš, Bischof.
The text was submitted by the authors in English.
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Loo, C.K., Peruš, M. & Bischof, H. Simulated quantum-optical object recognition from high-resolution images. Opt. Spectrosc. 99, 218–223 (2005). https://doi.org/10.1134/1.2034607
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DOI: https://doi.org/10.1134/1.2034607