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Proceedings Paper

Distortion-invariant class-associative multiple target detection using fractional power fringe-adjusted joint transform correlator
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Paper 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.

Paper Details

Date Published: 21 September 2004
PDF: 9 pages
Proc. SPIE 5426, Automatic Target Recognition XIV, (21 September 2004); doi: 10.1117/12.541707
Show Author Affiliations
Sharif M. A. Bhuiyan, Univ. of South Alabama (United States)
M. Nazrul Islam, Bangladesh Univ. of Engineering and Technology (Bangladesh)
Mohammad S. Alam, Univ. of South Alabama (United States)

Published in SPIE Proceedings Vol. 5426:
Automatic Target Recognition XIV
Firooz A. Sadjadi, Editor(s)

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