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Article

A Novel Image Inpainting Method Used for Veneer Defects Based on Region Normalization

College of Mechanical and Electrical Engineering, Northeast Forestry University, Harbin 150040, China
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Author to whom correspondence should be addressed.
Academic Editor: Nikolaos Doulamis
Sensors 2022, 22(12), 4594; https://doi.org/10.3390/s22124594
Received: 6 May 2022 / Revised: 11 June 2022 / Accepted: 16 June 2022 / Published: 17 June 2022
(This article belongs to the Section Electronic Sensors)
The quality of the veneer directly affects the quality and grade of a blockboard made of veneer. To improve the quality and utilization of a defective veneer, a novel deep generative model-based method is proposed, which can generate higher-quality inpainting results. A two-phase network is proposed to stabilize the network training process. Then, region normalization is introduced to solve the inconsistency problem between the mean and standard deviation, improve the convergence speed of the model, and prevent the model gradient from exploding. Finally, a hybrid dilated convolution module is proposed to reconstruct the missing areas of the panels, which alleviates the gridding problem by changing the dilation rate. Experiments on our dataset prove the effectiveness of the improved approach in image inpainting tasks. The results show that the PSNR of the improved method reaches 33.11 and the SSIM reaches 0.93, which are superior to other methods. View Full-Text
Keywords: image inpainting; veneer defect; region normalization; hybrid dilated convolution image inpainting; veneer defect; region normalization; hybrid dilated convolution
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MDPI and ACS Style

Ge, Y.; Chen, J.; Lou, Y.; Cui, M.; Zhou, H.; Zhou, H.; Sun, L. A Novel Image Inpainting Method Used for Veneer Defects Based on Region Normalization. Sensors 2022, 22, 4594. https://doi.org/10.3390/s22124594

AMA Style

Ge Y, Chen J, Lou Y, Cui M, Zhou H, Zhou H, Sun L. A Novel Image Inpainting Method Used for Veneer Defects Based on Region Normalization. Sensors. 2022; 22(12):4594. https://doi.org/10.3390/s22124594

Chicago/Turabian Style

Ge, Yilin, Jiahao Chen, Yunyi Lou, Mingdi Cui, Hongju Zhou, Hongwei Zhou, and Liping Sun. 2022. "A Novel Image Inpainting Method Used for Veneer Defects Based on Region Normalization" Sensors 22, no. 12: 4594. https://doi.org/10.3390/s22124594

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