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

Sharif M. A. Bhuiyan; M. Nazrul Islam; Mohammad S. Alam

doi:10.1117/12.541707

21 September 2004 Distortion-invariant class-associative multiple target detection using fractional power fringe-adjusted joint transform correlator

Sharif M. A. Bhuiyan, M. Nazrul Islam, Mohammad S. Alam

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Proceedings Volume 5426, Automatic Target Recognition XIV; (2004) https://doi.org/10.1117/12.541707
Event: Defense and Security, 2004, Orlando, Florida, United States

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.

Citation Download Citation

Sharif M. A. Bhuiyan, M. Nazrul Islam, and 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); https://doi.org/10.1117/12.541707

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KEYWORDS

Target detection

Distortion

Joint transforms

Target recognition

Binary data

Detection and tracking algorithms

Fourier transforms

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