Research on character recognition technology based on deep learning

Authors

  • Daodong Xiang

DOI:

https://doi.org/10.54097/fcis.v2i2.3933

Keywords:

Deep learning, Character recognition technology, Complex background

Abstract

In the security field, it is necessary to extract the information of each camera in real time. However, due to various reasons, each camera may have wrong shooting time, location and other information during the use process. If it cannot be found in time, it will bring great hidden danger to the security. This research based on CRNN depth learning algorithm to detect and recognize the text information on these pictures, and the results can effectively improve the accuracy of recognition.

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References

Zhang Tingting. Based on Tesseract_ Research on OCR character recognition system [D]. Nanjing: Nanjing University of Posts and Telecommunications, 2020.

Wang Yiwen. Research on the Application of Deep Convolution Neural Network in OCR [D]. Chengdu: University of Electronic Science and Technology of China, 2018.

Wang Yang, Li Zhendong, Yang Guanci. Research on the application of OCR character recognition based on deep learning in the banking industry [J]. Computer Application Research, 2020.

Zhao Shanshan. Design and implementation of image form data recognition system based on OCR technology[D]. Nanjing: Southeast University, 2020.

Zeng Yue, Ma Mingdong. Research on character recognition based on Tesseract_OCR [J]. Computer Technology and Development, 2021.

Xiao Jian. Learning Based OCR Character Recognition [J]. The Computer Age, 2018.

Han Ping, Liu Zexu. An Improved Method of X-ray Baggage Image Enhancement Based on Gray Level Grouping [J]. Journal of Civil Aviation University of China, 2011, 29 (4): 23-26.

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Published

26-12-2022

Issue

Section

Articles

How to Cite

Xiang, D. (2022). Research on character recognition technology based on deep learning. Frontiers in Computing and Intelligent Systems, 2(2), 50-52. https://doi.org/10.54097/fcis.v2i2.3933