Paper
6 March 2002 Class-associative multiple-target detection using fringe-adjusted joint transform correlation
Mohammad S. Alam, Mohammed Moseeur Rahman
Author Affiliations +
Abstract
We propose a class-associative correlation filter based technique for detecting a class of objects consisting of dissimilar patterns. The fringe-adjusted joint transform correlation algorithm is utilized to enhance the correlation performance, thus ensuring strong and equal correlation peak for each element of the selected class. For enhanced performance, an enhanced version of the fringe-adjusted filter is incorporated in the class-associative multiple target detection process. The feasibility of the proposed technique has been tested by computer simulation.
© (2002) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Mohammad S. Alam and Mohammed Moseeur Rahman "Class-associative multiple-target detection using fringe-adjusted joint transform correlation", Proc. SPIE 4734, Optical Pattern Recognition XIII, (6 March 2002); https://doi.org/10.1117/12.458406
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KEYWORDS
Target detection

Detection and tracking algorithms

Fourier transforms

Joint transforms

Computer simulations

Image filtering

Algorithm development

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