Publication detail

Sensor planning system for fringe projection scanning of sheet metal parts

KOUTECKÝ, T. PALOUŠEK, D. BRANDEJS, J.

Original Title

Sensor planning system for fringe projection scanning of sheet metal parts

English Title

Sensor planning system for fringe projection scanning of sheet metal parts

Type

journal article in Web of Science

Language

en

Original Abstract

Sensor planning system for scanning of parts with shiny surfaces is proposed. Reflectance model is used to simulate visual properties of the surface. Reflectivity function model fitted to the experimentally obtained material data. Detailed simulation and comparison of simulation and scanning is presented.

English abstract

Sensor planning system for scanning of parts with shiny surfaces is proposed. Reflectance model is used to simulate visual properties of the surface. Reflectivity function model fitted to the experimentally obtained material data. Detailed simulation and comparison of simulation and scanning is presented.

Keywords

3D scanning; Sensor planning; Automation; Reflective surfaces; Fringe projection; Sheet metal parts

Released

01.12.2016

Publisher

Elsevier

Location

Amsterdam, Nizozemsko

ISBN

0263-2241

Periodical

MEASUREMENT, Journal of the International Measurement Confederation (IMEKO)

Year of study

94

Number

December 2016

State

GB

Pages from

60

Pages to

70

Pages count

11

URL

Documents

BibTex


@article{BUT127134,
  author="Tomáš {Koutecký} and David {Paloušek} and Jan {Brandejs}",
  title="Sensor planning system for fringe projection scanning of sheet metal parts",
  annote="Sensor planning system for scanning of parts with shiny surfaces is proposed. Reflectance model is used to simulate visual properties of the surface. Reflectivity function model fitted to the experimentally obtained material data. Detailed simulation and comparison of simulation and scanning is presented.",
  address="Elsevier",
  chapter="127134",
  doi="10.1016/j.measurement.2016.07.067",
  howpublished="print",
  institution="Elsevier",
  number="December 2016",
  volume="94",
  year="2016",
  month="december",
  pages="60--70",
  publisher="Elsevier",
  type="journal article in Web of Science"
}