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Study on Text Irregular Image Algorithm Based on Convolutional Neural Network

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DOI: 10.23977/autml.2023.040109 | Downloads: 30 | Views: 603

Author(s)

Aisi Luo 1, Zeyu Jia 1, Hongyu Fu 1, Sheng Han 1

Affiliation(s)

1 Hebei University of Science & Technology, Yuxiang Street, Shijiazhuang, 050024, China

Corresponding Author

Aisi Luo

ABSTRACT

In view of character defects due to irregular interference of text images, this paper proposed a restoration algorithm model based on convolutional neural network and key point detection, implements restoration training on the defective character areas. By studying and analyzing the characteristics of ancient text images of different styles, a digital text image database was established. Based on the Chinese character regional positioning technology and key point detection technology, the restoration effect was evaluated and the training test was conducted after restoration of defective strokes.

KEYWORDS

Key point detection, convolutional neural network, Chinese character regional positioning technology, optical character recognition

CITE THIS PAPER

Aisi Luo, Zeyu Jia, Hongyu Fu, Sheng Han, Study on Text Irregular Image Algorithm Based on Convolutional Neural Network. Automation and Machine Learning (2023) Vol. 4: 57-62. DOI: http://dx.doi.org/10.23977/autml.2023.040109.

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