Institutional Repository of Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
Geometric Rectification of Document Images using Adversarial Gated Unwarping Network | |
Xiyan Liu1,2; Gaofeng Meng1,2; Bin Fan1,3; Shiming Xiang1,2; Chunhong Pan1 | |
发表期刊 | Pattern Recognition |
2020 | |
卷号 | 108期号:108页码:1-13 |
摘要 | Document images captured in natural scenes with a hand-held camera often suffer from geometric distortions and cluttered backgrounds. In this paper, we propose a simple yet efficient deep model named Adversarial Gated Unwarping Network (AGUN) to rectify these images. In this model, the rectification task is recast as a dense grid prediction problem. We thereby develop a pyramid encoder-decoder architecture to predict the unwarping grid at multiple resolutions in a coarse-to-fine fashion. Based on the observation that the structural visual cues, e.g., text-lines, text blocks, lines in tables, which are critical for the estimation of unwarping mapping, are non-uniformly distributed in the images, three gated modules are introduced to guide the network focusing on these informative cues rather than other interferences such as blank areas and complex backgrounds. To generate more visually pleasing rectification results, we further adopt adversarial training mechanism to implicitly constrain the unwarping grid estimation. Our model can rectify arbitrarily distorted document images with complicated page layouts and cluttered backgrounds. Experiments on the public benchmark dataset and the synthetic dataset demonstrate that our approach outperforms the state-of-the-art methods in terms of OCR accuracy and several widely used quantitative evaluation metrics. |
关键词 | Distorted document image Geometric rectification Gated module Deep learning |
收录类别 | SCI |
语种 | 英语 |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/46641 |
专题 | 模式识别国家重点实验室_先进时空数据分析与学习 |
通讯作者 | Gaofeng Meng |
作者单位 | 1.National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences 2.School of Artificial Intelligence, University of Chinese Academy of Sciences 3.School of Automation and Electrical Engineering, University of Science and Technology Beijing |
第一作者单位 | 模式识别国家重点实验室 |
通讯作者单位 | 模式识别国家重点实验室 |
推荐引用方式 GB/T 7714 | Xiyan Liu,Gaofeng Meng,Bin Fan,et al. Geometric Rectification of Document Images using Adversarial Gated Unwarping Network[J]. Pattern Recognition,2020,108(108):1-13. |
APA | Xiyan Liu,Gaofeng Meng,Bin Fan,Shiming Xiang,&Chunhong Pan.(2020).Geometric Rectification of Document Images using Adversarial Gated Unwarping Network.Pattern Recognition,108(108),1-13. |
MLA | Xiyan Liu,et al."Geometric Rectification of Document Images using Adversarial Gated Unwarping Network".Pattern Recognition 108.108(2020):1-13. |
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