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1 November 2011 Design of correlation filters for pattern recognition with disjoint reference image
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Correlation filters for pattern recognition are commonly designed under the assumption that the shape and appearance of an object of interest are explicitly known. In this paper, we consider a signal model in which an object of interest is given at unknown coordinates in a cluttered reference image and corrupted by additive noise. The reference image is used to design filters for detecting a target in scenes with a nonoverlapping background and additive noise. An optimum correlation filter with respect to peak-to-output energy for object detection is derived. The shape and appearance of the target are estimated from the reference image. Two methods to estimate the frequency response of the derived filter are used. Computer simulation results obtained with the proposed filters are presented and discussed. The performance of the filters is evaluated in terms of discrimination capability and location accuracy for different statistics of the backgrounds and noise processes present in the signal model.
©(2011) Society of Photo-Optical Instrumentation Engineers (SPIE)
Pablo Mario Aguilar-Gonzalez and Vitaly I. Kober "Design of correlation filters for pattern recognition with disjoint reference image," Optical Engineering 50(11), 117201 (1 November 2011).
Published: 1 November 2011


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