Algorithms of determining of bodies in a 3D irregular point cloud :: IKBFU's united scientific journal editorial office

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The real and legitimate goal of the sciences is the endowment of human life with new inventions and riches
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Algorithms of determining of bodies in a 3D irregular point cloud

Author Alsynbaev K
Pages 159-162
Article Download
Keywords a point cloud, Clustering, Voxel, micro-seismic monitoring, Recogni¬tion algorithms, Bresenham's line algorithm
Abstract (summary) A technique for recognition of shapes of bodies in a 3D point cloud is de-scribed. At the first step cloud clustering is conducted using the criterion of maximum distance between the points to identify the bodies being determined. Then proceeding to voxel presentation is being done. Existence of a tetrahe-dron with its points in cloud points and size-limited sides for which the voxel being tested is internal is treated as a criterion of belongment of voxel to a body. A fast algorithm for voxel tetrahedron filling is developed and used for optimization. The work is a part of software for micro-seismic monitoring data processing.
References 1. Алсынбаев К. С., Козлов А. В. Средства распознавания и визуализации раз¬ломов и зон техногенной трещиноватости на основе обработки данных микро¬сейсмического мониторинга // Вестник Балтийского федерального университета им. И. Канта. 2014. Вып. 4. С. 127—134.
2. Боровиков С. Н., Иванов И. Э., Крюков И. А. Построение тетраэдризации Делоне с ограничениями для тел с криволинейными границами // Журнал вычислительной математики и математической физики. 2005. Т. 45, № 8. С. 1407—1423.
3. Суков С. А. Методы генерации тетраэдральных сеток и их программные реализации // Препринты ИПМ им. М. В. Келдыша. 2015. № 23.
4. Baidurja Ray, Avi Lin, Jianfu Ma. Unconventional micro-seismicity based en-hanced 3D SRV estimator using advanced parameter-free concave methodology // SEG Technical Program Expanded Abstracts. 2014. P. 2304–2308.
5. Кластеризация точек на регулярной сети. URL: http://habrahabr.ru/post/ 138185/ (дата обращения: 19.08.2015).

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