Article in Russian
For citation: Ponomarev S.V. Study of edge detection techniques in 3D image matching problem.
Scientific and Technical Journal of Information Technologies, Mechanics and Optics, 2017, vol. 17, no. 4, pp. 694–701 (in Russian). doi: 10.17586/2226-1494-2017-17-4-694-701
Abstract
The paper deals withthe problem of image matching in three-dimensional space using contour description. An object-independent hierarchical structural juxtaposition algorithm is proposed. It is based on 2D structural matching algorithm using an alphabet of simple object-independent contour structural elements. This algorithm proved to be sufficiently robust and reliable for matching successfully the pictures of natural landscapes taken in differing seasons from differing aspect angles by differing sensors (the visible optical, IR, and SAR pictures, as well as the depth maps and geographical vector-type maps), but was unable to compare images of three-dimensional scenes, where it is required to apply different models of geometric transformations to different parts of the image. The three-dimensional version of the algorithm gives the possibility to overcome this limitation, but it is less robust with relation to changes in aspect angles. One of the key stages of the presented algorithm is the building of 3D scene contour descriptions. In order to increase the robustness of the algorithm a study of 3D edge detection techniques is carried out. The quantitative estimation of accuracy and speed of the presented techniques is given. The modification of the 3D structural matching algorithm based on the results of the study is proposed. The developed technique can be used for automatic navigation of extremely low flying unmanned vehicles or autonomous terrestrial robots in view of conditions with high degree a priori scene uncertainty.
Keywords: structural matching, image alignment, edge detection, three-dimensional space
Acknowledgements. The work was supported by the RF Ministry of Education and Science, and partially by the Government of the Russian Federation (grant 074-U01).
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