Distortion-invariant multiple target detection using class-associative joint transform correlation

Sharif Md. Ataullah Bhuiyan; Mohammed Nazrul Islam; Muhammad Zulfïker Alam

doi:10.1117/1.2042475

1 September 2005 Distortion-invariant multiple target detection using class-associative joint transform correlation

Sharif Md. Ataullah Bhuiyan, Mohammed Nazrul Islam, Muhammad Zulfïker Alam

Author Affiliations +

Optical Engineering, Vol. 44, Issue 9, 097201 (September 2005). https://doi.org/10.1117/1.2042475

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.

©(2005) Society of Photo-Optical Instrumentation Engineers (SPIE)

Citation Download Citation

Sharif Md. Ataullah Bhuiyan, Mohammed Nazrul Islam, and Muhammad Zulfïker Alam "Distortion-invariant multiple target detection using class-associative joint transform correlation," Optical Engineering 44(9), 097201 (1 September 2005). https://doi.org/10.1117/1.2042475

Published: 1 September 2005

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