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Proceedings Paper

Harmogram feature sets for 1D and 2D data
Author(s): Orgal Thomas Holland; Wendy L. Poston
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Paper Abstract

The harmogram is calculated from the power spectral density and an estimate of background noise. It is a computationally effective means of analyzing a signal for constituent periodicities. For one-dimensional signals it can (1) provide a means to determine the likelihood that a periodic component is present and (2) determine its principal frequency and related harmonics. The mathematical foundations of the harmogram have recently been extended to two-dimensional signals where it provides interesting insight into images (e.g., texture and composition). In either case, the harmogram produces a much reduced invariant feature set which is useful as a preprocess to classification. This presentation details the harmogram process and illustrates its application with several examples.

Paper Details

Date Published: 17 July 1998
PDF: 12 pages
Proc. SPIE 3374, Signal Processing, Sensor Fusion, and Target Recognition VII, (17 July 1998); doi: 10.1117/12.327117
Show Author Affiliations
Orgal Thomas Holland, Naval Surface Warfare Ctr. (United States)
Wendy L. Poston, Naval Surface Warfare Ctr. (United States)


Published in SPIE Proceedings Vol. 3374:
Signal Processing, Sensor Fusion, and Target Recognition VII
Ivan Kadar, Editor(s)

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