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Optical Engineering

Distortion-invariant multiple target detection using class-associative joint transform correlation
Author(s): Sharif Md. Ataullah Bhuiyan; Mohammed Nazrul Islam; Muhammad Zulfïker Alam
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Paper Abstract

A distortion-invariant class-associative pattern recognition technique is proposed, where a class of objects may be defined as a group of objects with similarity and dissimilarity among them. The fractional power fringe-adjusted joint transform correlation technique as well as the synthetic discriminant function concept has been effectively utilized to achieve the distortion-invariant detection of multiple dissimilar targets simultaneously present in the input scene. Simulation results prove that the proposed scheme is an effective tool for the detection of multiple dissimilar targets in both binary and gray-level input scenes corrupted by distortion and noise.

Paper Details

Date Published: 1 September 2005
PDF: 10 pages
Opt. Eng. 44(9) 097201 doi: 10.1117/1.2042475
Published in: Optical Engineering Volume 44, Issue 9
Show Author Affiliations
Sharif Md. Ataullah Bhuiyan, Univ. of South Alabama (United States)
Mohammed Nazrul Islam, Univ. of South Alabama (United States)
Muhammad Zulfïker Alam, Bangladesh Univ. of Engineering and Technology (Bangladesh)

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