Publikace detail

Advanced Plane Properties by Using Level Image

Autoři: Chmelař Pavel | Beran Ladislav | Chmelařová Natalija | Rejfek Luboš

Rok: 2018

Druh publikace: článek ve sborníku

Název zdroje: 28th International Conference Radioelektronika, RADIOELEKTRONIKA 2018

Název nakladatele: IEEE (Institute of Electrical and Electronics Engineers)

Místo vydání: New York

Strana od-do: 1-6

Tituly:

Jazyk	Název	Abstrakt	Klíčová slova
cze	Pokročilé vlastnosti roviny získané úrovňovým obrazem	This paper deals with advanced plane properties in analyzed point clouds. Planes are detected by the level connected component labeling, which is our modification of the classical algorithm for 3D data. According selected detection parameters and a scanning dimension the algorithm detects individual levels in an input point cloud. A level is presented by an image expressing the points’ presence at a specific level in a space, we call it level image. The pixel size in a level image is equal to the point cloud distance quantization. This connection allows us to use image processing methods to get important properties about the analyzed 3D space, which can be difficult to get by the standard mathematical solution. Image processing methods offers a simple plane segmentation and visualization or area and perimeter estimation including statistical data description. The results show level image advantages.	detekce roviny; úrovňový obraz; úrovňové označování spojených komponent; mračno bodů; odhad plochy a obvodu
eng	Advanced Plane Properties by Using Level Image	This paper deals with advanced plane properties in analyzed point clouds. Planes are detected by the level connected component labeling, which is our modification of the classical algorithm for 3D data. According selected detection parameters and a scanning dimension the algorithm detects individual levels in an input point cloud. A level is presented by an image expressing the points’ presence at a specific level in a space, we call it level image. The pixel size in a level image is equal to the point cloud distance quantization. This connection allows us to use image processing methods to get important properties about the analyzed 3D space, which can be difficult to get by the standard mathematical solution. Image processing methods offers a simple plane segmentation and visualization or area and perimeter estimation including statistical data description. The results show level image advantages.	plane detection; level image; level connected component labeling; point cloud; area and perimeter estimation

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