I.N. Ischuk – Dr. Sc. (Eng.), Associate Professor, Head of Department, MESC «Zhukovsky–Gagarin Air Force Academy» (Voronezh)
A.M. Filimonov – Post-graduate Student, MESC «Zhukovsky–Gagarin Air Force Academy» (Voronezh)
E.A. Stepanov – Post-graduate Student, MESC «Zhukovsky–Gagarin Air Force Academy» (Voronezh)
K.V. Postnov – Post-graduate Student, MESC «Zhukovsky–Gagarin Air Force Academy» (Voronezh)
Modern systems of detection of man-made objects on the earth's surface in the infrared wavelength range of search for objects by analyzing the thermal contrasts. This approach is not always able to detect an object, as the contrasts between the man-made object and the background (man-made or natural landscape) change over time.
The aim is to increase the efficiency of detection, identification and subsequent classification of objects according to the dynamic IR images from UAVs.
Since the magnitude of thermal contrasts are largely determined by thermo-physical parameters of the materials that make up the objects for solving the detection problem it is necessary to use a new approach, which is based on the determination of thermal con-ductivity and thermal diffusivity of materials constituting the object.
This approach is implemented in the method of classification of stationary and quasi-stationary objects based on background and ref-erence materials on the basis of the construction of thermal tomograms according to the dynamic IR images obtained complexes with UAVs. The method relates to an automated method for decoding and allows classification of objects on the new telltale signs - thermal parameters (thermal conductivity and thermal diffusivity). The totality of the estimated values of thermal conductivity and thermal diffusivity obtained for remote measurement of the temperature distribution of the radiation field with the help of thermal imaging receiver form a discrete set, over which the classification. Classification is the point estimate of the pixel supplies thermal tomography in the image to a class based on the maximum likelihood method.
Natural experiment to assess the visibility of the two short-range UAV airframes was conducted to test the method of classification of stationary and quasi-stationary objects based on background and reference materials in vivo. Set IR images of the site area was ob-tained quadrocopters during periodic shooting. In accordance with the article in the stages of the process of object classification was calculated tomography study on the thermal conductivity of the surface.
In the course of solving classification problems resulting tomograms built its histogram, which showed that the distribution of the es-timated values of thermal conductivity are grouped near the thermal conductivity values of the corresponding reference materials with the minimum standard deviation. In this regard, the search facilities on the distribution of the estimated values of the thermal conductivity is more effective, as it allows easily divide objects into classes. Using the new method of classifying objects by thermal parameters allowed in the field experiment with higher quality, not only to recognize objects placed on the ground, but also to highlight areas that were not visible on the IR image contrast.
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