21 September 2004 Distortion-invariant class-associative multiple target detection using fractional power fringe-adjusted joint transform correlator
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Abstract
Class-associative detection involves recognition of multiple dissimilar targets simultaneously present in the input scene. In this paper, synthetic discriminant function (SDF) has been incorporated in the fringe-adjusted joint transform correlation based class-associative target detection technique to make it distortion invariant. The concept of fractional power fringe-adjusted joint transform correlation (FPFJTC) has been utilized both to generate the SDF based reference images and to detect the class-associative targets using multi-target detection algorithm. FPFJTC provides mainly three different types of filters, may be termed as generalized fringe-adjusted filters (GFAF), to modify the joint power spectrum and thus facilitates the selection of appropriate filter/filters. Here we have proposed the phase-only filter variation from the GFAF at all steps for successful detection. Simulation results verify that the proposed scheme performs satisfactorily in detecting both binary and gray level images of a class irrespective of distortion.
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Sharif M. A. Bhuiyan, Sharif M. A. Bhuiyan, M. Nazrul Islam, M. Nazrul Islam, Mohammad S. Alam, Mohammad S. Alam, } "Distortion-invariant class-associative multiple target detection using fractional power fringe-adjusted joint transform correlator", Proc. SPIE 5426, Automatic Target Recognition XIV, (21 September 2004); doi: 10.1117/12.541707; https://doi.org/10.1117/12.541707
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