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Proceedings Paper

Human target identification and automated shape based target recognition algorithms using target silhouette
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Paper Abstract

Human target identification performance based on target silhouettes is measured and compared to that of complete targets. The target silhouette identification performance of automated region based and contour based shape identification algorithms are also compared. The region based algorithms of interest are Zernike Moment Descriptor (ZMD), Geometric Moment Descriptor (GMD), and Grid Descriptor (GD) while the contour based algorithms considered are Fourier Descriptor (FD), Multiscale Fourier Descriptor (MFD), and Curvature Scale Space Descriptor (CS). The results from the human perception experiments indicate that at high levels of degradation, human identification of target based on silhouettes is better than that of complete targets. The shape recognition algorithm comparison shows that GD performs best, very closely followed by ZMD. In general region based shape algorithms perform better that contour based shape algorithms.

Paper Details

Date Published: 11 April 2008
PDF: 9 pages
Proc. SPIE 6941, Infrared Imaging Systems: Design, Analysis, Modeling, and Testing XIX, 69410B (11 April 2008); doi: 10.1117/12.777337
Show Author Affiliations
Srikant K. Chari, The Univ. of Memphis (United States)
Carl E. Halford, The Univ. of Memphis (United States)
Eddie Jacobs, The Univ. of Memphis (United States)


Published in SPIE Proceedings Vol. 6941:
Infrared Imaging Systems: Design, Analysis, Modeling, and Testing XIX
Gerald C. Holst, Editor(s)

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