Stability indices and evaluation of an algorithm for recognizing the type of a dynamic object detected on a finite sequence of 2D baseline frames of an optoelectronic device

Yagolnikov, S.V., Khramichev, A.A., Katulev, A.N.

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For Russian citation (Opticheskii Zhurnal):

Ягольников С.В., Храмичев А.А., Катулев А.Н. Показатели и оценка устойчивости алгоритма распознавания типа динамического объекта, обнаруживаемого на конечной последовательности 2D фоноцелевых кадров оптико-электронного прибора // Оптический журнал. 2018. Т. 85. № 5. С. 34–45. http://doi.org/10.17586/1023-5086-2018-85-05-34-45

Yagolnikov S.V., Khramichev A.A., Katulev A.N. Stability indices and evaluation of an algorithm for recognizing the type of a dynamic object detected on a finite sequence of 2D baseline frames of an optoelectronic device [in Russian] // Opticheskii Zhurnal. 2018. V. 85. № 5. P. 34–45. http://doi.org/10.17586/1023-5086-2018-85-05-34-45

For citation (Journal of Optical Technology):

S. V. Yagol’nikov, A. A. Khramichev, and A. N. Katulev, "Stability indices and evaluation of an algorithm for recognizing the type of a dynamic object detected on a finite sequence of 2D baseline frames of an optoelectronic device," Journal of Optical Technology. 85(5), 281-290 (2018). https://doi.org/10.1364/JOT.85.000281

Abstract:

This paper proposes robustness indices for an algorithm for recognizing the type of a dynamic object and a probability-distribution law for the sufficient recognition statistics formed by the algorithm when there is a priori indeterminacy. The law is used to validate the algorithm. The wavelet–fractal-correlation algorithm implements a vector criterion of the ratios of the likelihood functions of simple alternative hypotheses—the types of objects invariant to the features of their trajectories. The likelihood functions are reconstituted by modeling over assemblages of implementations of fractal dimensions, energies of the wavelet spectra, and the maximum eigenvalues of displaced correlation matrices as functionals of the coordinates of the spatial position of various types of actual objects measured by an optoelectronic device. Modeling is used to confirm that the algorithm is stable and highly efficient.

Keywords:

algorithm, robustness, vector criterion, recognition statistics, type of dynamic object, algorithm efficiency

Acknowledgements:

The research was supported by the Ministry of Education and Science of the Russian Federation (Minobrnauka) (2.1777.2017).

OCIS codes: 1102960, 1002000

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