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17 July 1998 Harmogram feature sets for 1D and 2D data
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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.
© (1998) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Orgal Thomas Holland and Wendy L. Poston "Harmogram feature sets for 1D and 2D data", Proc. SPIE 3374, Signal Processing, Sensor Fusion, and Target Recognition VII, (17 July 1998);

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