Attention mechanism‑based text detection and recognition method for secondary circuit terminals

Authors

Ming ZHONG, Inner Mongolia Power Research Institute, Hohhot 010020, China;Inner Mongolia Autonomous Region Power System Intelligent Grid Simulation Enterprise Key Laboratory, Hohhot 010020, China
Jun TAO, Inner Mongolia Power Research Institute, Hohhot 010020, China;Inner Mongolia Autonomous Region Power System Intelligent Grid Simulation Enterprise Key Laboratory, Hohhot 010020, China
Minfu A, Inner Mongolia Power Research Institute, Hohhot 010020, China;Inner Mongolia Autonomous Region Power System Intelligent Grid Simulation Enterprise Key Laboratory, Hohhot 010020, China
Yi YANG, Inner Mongolia Power Research Institute, Hohhot 010020, China;Inner Mongolia Autonomous Region Power System Intelligent Grid Simulation Enterprise Key Laboratory, Hohhot 010020, China

Keywords

secondary circuit of substation; image recognition; attention mechanism; feature extraction; text recognition

Abstract

The secondary circuit of the substation is the basis of the secondary advanced integrated business. The automatic feature recognition and information extraction of the secondary circuit by image recognition technology can realize the secondary circuit's intelligent operation and maintenance business. However, the images collected by the substation have messy backgrounds, low resolution, and distortion, making it very challenging to identify irregular text using image recognition technology. Therefore, a text detection and recognition method of a secondary loop terminal based on an attention mechanism is proposed. This method mainly includes preprocessing, text detection, and text recognition. In the text recognition part, a spatiotemporal embedding encoding method is proposed, which can better use the picture's location information. Compared with the unimproved method, only the sequence‑level annotation information is needed in the training process, and no additional fine‑grained character level box or segmentation mask is needed. Finally, it is proved that the proposed method is not only easy to use and has good performance but is also better than other methods in recognition accuracy.

DOI

10.19781/j.issn.1673-9140.2023.03.014

First Page

132

Last Page

139

Recommended Citation

ZHONG, Ming; TAO, Jun; A, Minfu; and YANG, Yi (2023) "Attention mechanism‑based text detection and recognition method for secondary circuit terminals," Journal of Electric Power Science and Technology: Vol. 38: Iss. 3, Article 14.
DOI: 10.19781/j.issn.1673-9140.2023.03.014
Available at: https://jepst.researchcommons.org/journal/vol38/iss3/14