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3D-scanning for rapid prototyping

Keywords:

A. Yu. Aksenov – Junior Research Scientist, Laboratory of Research Automation, St. Petersburg Institute for Informatics and Automation of the Russian Academy of Sciences (SPIIRAS). E-mail: a_aksenov@mail.iias.spb.su, sial.iias.spb.su
V. V. Alexandrova – Ph.D. (Ped.), Research Scientist, Laboratory of Research Automation St. Petersburg Institute for Informatics and Automation of the Russian Academy of Sciences (SPIIRAS). E-mail: alexandr@iias.spb.su
A. A. Zaytseva – Ph.D. (Eng.), Senior Research Scientist, Laboratory of Research Automation, St. Petersburg Institute for Informatics and Automation of the Russian Academy of Sciences (SPIIRAS). E-mail: cher@iias.spb.su


3D-data can be obtained in several ways: modeling, scanning, application of tomography 3D-recovery from several 2D images. Depending on data obtaining method the resulting bit volume of data will greatly differs. For efficient storage of 3D-objects the representation methods based on object class are needed. The paper proposes the method of point cloud compression based on space subdivision by 256×256×256 cells and it’s further bit stream representation based on space filling curve scanning and secondary compression. The point cloud obtained through 3D-scanning consists of compact regions of space which are corresponding to surfaces of scanned object, therefore the implementation of Gilbert’s space filling curve for 1D bit stream representation has great effect on secondary compression. The proposed method can be applied in 3D-scanning, processing and printing software, efficient storage of 3D-objects spatial data, systems of cognitive programming, reducing cost of data transmission.
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