Detail publikace

Visible Light Communication transmitter position detection for use in ITS

Originální název

Visible Light Communication transmitter position detection for use in ITS

Anglický název

Visible Light Communication transmitter position detection for use in ITS

Jazyk

en

Originální abstrakt

This paper presents three major Visible Light Communication (VLC) transmitter LED detection techniques and proposes a new detection method based on the fusion of their outputs. Statistics of each detection technique are used to estimate their outputs' likelihood, which is then used for weighted averaging of their results and to provide more robust detection output than the state of the art. An analytical model of the entire detection system is provided and a practical simulation using Open Computer Vision (OpenCV) and Python language is performed.

Anglický abstrakt

This paper presents three major Visible Light Communication (VLC) transmitter LED detection techniques and proposes a new detection method based on the fusion of their outputs. Statistics of each detection technique are used to estimate their outputs' likelihood, which is then used for weighted averaging of their results and to provide more robust detection output than the state of the art. An analytical model of the entire detection system is provided and a practical simulation using Open Computer Vision (OpenCV) and Python language is performed.

BibTex


@article{BUT147361,
  author="Marek {Novák} and Aleš {Dobesch} and Otakar {Wilfert} and Lukáš {Janík}",
  title="Visible Light Communication transmitter position detection for use in ITS",
  annote="This paper presents three major Visible Light Communication (VLC) transmitter LED detection techniques and proposes a new detection method based on the fusion of their outputs. Statistics of each detection technique are used to estimate their outputs' likelihood, which is then used for weighted averaging of their results and to provide more robust detection output than the state of the art. An analytical model of the entire detection system is provided and a practical simulation using Open Computer Vision (OpenCV) and Python language is performed.",
  address="Elsevier",
  chapter="147361",
  doi="10.1016/j.osn.2018.04.002",
  howpublished="online",
  institution="Elsevier",
  number="2",
  year="2018",
  month="may",
  pages="1--8",
  publisher="Elsevier",
  type="journal article"
}