Correlation pattern recognition in nonoverlapping scene using a noisy reference

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Abstract

Correlation filters for recognition of a target in nonoverlapping background noise are proposed. The object to be recognized is given implicitly; that is, it is placed in a noisy reference image at unknown coordinates. For the filters design two performance criteria are used: signalto-noise ratio and peak-to-output energy. Computer simulations results obtained with the proposed filters are discussed and compared with those of classical correlation filters in terms of discrimination capability. © 2009 Springer-Verlag Berlin Heidelberg.

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Aguilar-González, P. M., & Kober, V. (2009). Correlation pattern recognition in nonoverlapping scene using a noisy reference. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5856 LNCS, pp. 555–562). https://doi.org/10.1007/978-3-642-10268-4_65

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