УДК: 004.932.2, 517.968

Wavelet/fractal correlation algorithm for type recognition of a dynamic object detected by an optoelectronic device

Publication in Journal of Optical Technology

For Russian citation (Opticheskii Zhurnal):

Катулев А.Н., Храмичев А.А. Вейвлет-фрактально-корреляционный алгоритм распознавания типа динамического объекта, обнаруживаемого оптико-электронным прибором // Оптический журнал. 2017. Т. 84. № 4. С. 25–34.

Katulev A.N., Khramichev A.A. Wavelet/fractal correlation algorithm for type recognition of a dynamic object detected by an optoelectronic device [in Russian] // Opticheskii Zhurnal. 2017. V. 84. № 4. P. 25–34.

For citation (Journal of Optical Technology):

A. N. Katulev and A. A. Khramichev, "Wavelet/fractal correlation algorithm for type recognition of a dynamic object detected by an optoelectronic device," Journal of Optical Technology. 84(4), 237-245 (2017). https://doi.org/10.1364/JOT.84.000237

Abstract:

We propose an algorithm for automated type recognition of dynamic objects using observations performed by an optoelectronic device against a natural background. This algorithm is invariant with respect to the trajectories of the objects, is based on the ratio of the likelihood functions for simple alternative hypotheses, and implements an unbiased maximum-power criterion for object recognition with indeterminate a priori knowledge of the target environment. The likelihood functions are calculated over certain samples of wavelet-spectrum energies, fractal dimensions, and maximum auto-correlation-matrix eigenvalues for instrumentally measured elevation and azimuth, and the calculated maximum range of the object during a finite time interval. Modeling was used to establish that the algorithm has high computational efficiency for real-time use on modern PCs.

Keywords:

optoelectronic device, dynamic object type, recognition, recognition statistics, criterion, algorithm

OCIS codes: 110.2960, 100.2000

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