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

Artikel

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.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Journal: Energy Reports ; ISSN: 2352-4847 ; Volume: 5 ; Year: 2019 ; Pages: 842-852 ; Amsterdam: Elsevier

Classification and Topics

• Classification: Wirtschaft
• Subject: Data collection ; Displays ; Image databases ; Optical character recognition ; Smart metering ; Text recognition

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Kanagarathinam, Karthick ; Sekar, Kavaskar
• Event: Veröffentlichung
• (who): Elsevier
• (where): Amsterdam
• (when): 2019

Further information

• DOI: doi:10.1016/j.egyr.2019.07.004
• Handle: http://hdl.handle.net/10419/243632
• Last update: 10.03.2025, 11:41 AM CET