T. Y. Nikolaeva, N. V. Petrov

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The subject of study is the techniques of particle statistics evaluation, in particular, processing methods of particle images obtained by coherent illumination. This paper considers the problem of recognition and statistical accounting for individual images of small scattering particles in an arbitrary section of the volume in case of high concentrations. For automatic recognition of focused particles images, a special algorithm for statistical analysis based on contouring and thresholding was used. By means of the mathematical formalism of the scalar diffraction theory, coherent images of the particles formed by the optical system with high numerical aperture were simulated. Numerical testing of the method proposed for the cases of different concentrations and distributions of particles in the volume was performed. As a result, distributions of density and mass fraction of the particles were obtained, and the efficiency of the method in case of different concentrations of particles was evaluated. At high concentrations, the effect of coherent superposition of the particles from the adjacent planes strengthens, which makes it difficult to recognize images of particles using the algorithm considered in the paper. In this case, we propose to supplement the method with calculating the cross-correlation function of particle images from adjacent segments of the volume, and evaluating the ratio between the height of the correlation peak and the height of the function pedestal in the case of different distribution characters. The method of statistical accounting of particles considered in this paper is of practical importance in the study of volume with particles of different nature, for example, in problems of biology and oceanography. Effective work in the regime of high concentrations expands the limits of applicability of these methods for practically important cases and helps to optimize determination time of the distribution character and statistical characteristics of the particles.

Keywords: images processing, numerical simulation, particle image velocimetry

Acknowledgements. The work has been partially financially supported by the Government of the Russian Federation (grant 074-U01). N.V. Petrov expresses thanks to the Russian Federation Ministry of Education and Science for federal projects support (project № 2014/190) in the sphere of scientific activity within a basic part of the government order.

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