FrameNet: Tabular Image Preprocessing Based on UNet and Adaptive Correction
文献类型:会议论文
作者 | Wang YF(王宇飞)1,2; Du C(杜臣)1,2; Xiao BH(肖柏华)2 |
出版日期 | 2022-05 |
会议日期 | May 23–27, 2022 |
会议地点 | Lecce, Italy |
关键词 | Computer vision, Deep learning, Image rectification |
页码 | 407-417 |
英文摘要 | Detecting and recognizing objects in images with complex backgrounds and deformations is a challenging task. In this work, we propose FrameNet, while a deep table lines segmentation network based on our Res18UNet with an adaptive deformation correction algorithm for correcting the table lines. We use Itinerary/Receipt of E-ticket for Air Transport to evaluate our methods. The experiment results show that our Res18UNet can reduce the number of parameters and improve the speed of image segmentation without significantly reducing the segmentation accuracy, and our correction method can better correct the perspective deformation and some distorted tablular images with no dependence on pixel-level ground truth image. In addition, we also apply our model and method to VAT invoice dataset and prove that they also have better transfer ability |
会议录 | Image Analysis and Processing–ICIAP 2022: 21st International Conference |
会议录出版者 | Springer Cham |
会议录出版地 | Switzerland |
源URL | [http://ir.ia.ac.cn/handle/173211/51840] |
专题 | 自动化研究所_复杂系统管理与控制国家重点实验室_影像分析与机器视觉团队 |
通讯作者 | Xiao BH(肖柏华) |
作者单位 | 1.University of Chinese Academy of Sciences, Beijing, China 2.The State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China |
推荐引用方式 GB/T 7714 | Wang YF,Du C,Xiao BH. FrameNet: Tabular Image Preprocessing Based on UNet and Adaptive Correction[C]. 见:. Lecce, Italy. May 23–27, 2022. |
入库方式: OAI收割
来源:自动化研究所
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