Research of Super-resolution Processing of Invoice Image Based on Generative Adversarial Network

Authors

Xinli Li, School of Control and Computer Engineering, North China Electric Power University, Beijing, 102206, China;
Changming Zou, School of Control and Computer Engineering, North China Electric Power University, Beijing, 102206, China;
Guotian Yang, School of Control and Computer Engineering, North China Electric Power University, Beijing, 102206, China;
Liu He, School of Control and Computer Engineering, North China Electric Power University, Beijing, 102206, China;

Abstract

Abstract: Automatic identification of invoices can effectively improve financial efficiency. But low-resolution invoice image reduces the accuracy of automatic identification, an ESRGAN (Encoder Super-resolution Generative Adversarial Network) network for super-resolution processing of invoice images is proposed. The ESRGAN network is based on a conditional generative adversarial network. An auxiliary encoder is designed to guide the network to generate a more realistic super-resolution image. Based on the actual invoice image, the ESRGAN network and the conventional image processing, SRCNN (Super-resolution Convolutional Neural Networks) network and SRGAN (Super-resolution Generative Adversarial Network) network. The model is evaluated through two evaluation indicators of peak signal-to-noise ratio (PSNR) and structural similarity (SSIM). The experimental results show that the images processed based on ESRGAN super-resolution are better on visual effects and evaluation indicators.

Recommended Citation

Li, Xinli; Zou, Changming; Yang, Guotian; and He, Liu (2021) "Research of Super-resolution Processing of Invoice Image Based on Generative Adversarial Network," Journal of System Simulation: Vol. 33: Iss. 6, Article 9.
DOI: 10.16182/j.issn1004731x.joss.20-0095
Available at: https://dc-china-simulation.researchcommons.org/journal/vol33/iss6/9

First Page

1307

Revised Date

2020-05-02

DOI Link

https://doi.org/10.16182/j.issn1004731x.joss.20-0095

Last Page

1314

CLC

TP391.4

Recommended Citation

Li Xinli, Zou Changming, Yang Guotian, Liu He. Research of Super-resolution Processing of Invoice Image Based on Generative Adversarial Network[J]. Journal of System Simulation, 2021, 33(6): 1307-1314.

DOI

10.16182/j.issn1004731x.joss.20-0095