Artikel

Text detection and recognition in raw image dataset of seven segment digital energy meter display

The article describes the collection of the dataset of raw images of digital energy meters display, text detection and recognition of seven segment numerals from collected samples that may be helpful in reducing the cost of advanced metering infrastructure (AMI). The presented dataset has tremendous potentials in fully automated optical character recognition (OCR) based electricity billing. The dataset has been named as 'YUVA EB Dataset' that has the collection of digital energy meter images. The images have been captured under day and night light conditions. The research work on recognizing the text from seven segment display in energy meters has been carried out using our dataset under the challenging text recognition conditions like tilted position, blurred, day and night light captured images. MSER and labeling method based OCR algorithm has been used for text detection and recognition.

Sprache
Englisch

Erschienen in
Journal: Energy Reports ; ISSN: 2352-4847 ; Volume: 5 ; Year: 2019 ; Pages: 842-852 ; Amsterdam: Elsevier

Klassifikation
Wirtschaft
Thema
Data collection
Displays
Image databases
Optical character recognition
Smart metering
Text recognition

Ereignis
Geistige Schöpfung
(wer)
Kanagarathinam, Karthick
Sekar, Kavaskar
Ereignis
Veröffentlichung
(wer)
Elsevier
(wo)
Amsterdam
(wann)
2019

DOI
doi:10.1016/j.egyr.2019.07.004
Handle
Letzte Aktualisierung
10.03.2025, 11:41 MEZ

Datenpartner

Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.

Objekttyp

  • Artikel

Beteiligte

  • Kanagarathinam, Karthick
  • Sekar, Kavaskar
  • Elsevier

Entstanden

  • 2019

Ähnliche Objekte (12)