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Document image binarization with cascaded generators of conditional generative adversarial networks

文献类型：期刊论文

作者Zhao, Jinyuan1,2; Shi, Cunzhao1; Jia, Fuxi1; Wang, Yanna1; Xiao, Baihua1
刊名PATTERN RECOGNITION
出版日期2019-12-01
卷号96页码:12
关键词Cascaded generator Conditional generative adversarial networks Document image binarization Image generation Historical document analysis
ISSN号0031-3203
DOI10.1016/j.patcog.2019.106968
通讯作者Shi, Cunzhao(cunzhao.shi@ia.ac.cn)
英文摘要Binarization is often the first step in many document analysis tasks and plays a key role in the subsequent steps. In this paper, we formulate binarization as an image-to-image generation task and introduce the conditional generative adversarial networks (cGANs) to solve the core problem of multi-scale information combination in binarization task. Our generator consists of two stages: In the first stage, sub generator Cl learns to extract text pixels from an input image. Different scales of the input image are processed by G1 and corresponding binary images are generated. In the second stage, our sub-generator G2 learns a combination of results at different scales from the first stage and produces the final binary result. We conduct comprehensive experiments of the proposed method on nine public document image binarization datasets. Experimental results show that compared with many classical and state-of-the-art approaches, our method gains promising performance in the accuracy and robustness of binarization. (C) 2019 Elsevier Ltd. All rights reserved.
WOS关键词COMPETITION
资助项目National Natural Science Foundation of China (NSFC)[71621002] ; Key Programs of the Chinese Academy of Sciences[ZDBS-SSW-JSC003] ; Key Programs of the Chinese Academy of Sciences[ZDBS-SSW-JSC004] ; Key Programs of the Chinese Academy of Sciences[ZDBS-SSW-JSC005]
WOS研究方向Computer Science ; Engineering
语种英语
WOS记录号WOS:000487569700014
出版者ELSEVIER SCI LTD
资助机构National Natural Science Foundation of China (NSFC) ; Key Programs of the Chinese Academy of Sciences
源URL[http://ir.ia.ac.cn/handle/173211/26681]  
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Shi, Cunzhao
作者单位1.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
2.Univ Chinese Acad Sci, Beijing, Peoples R China
推荐引用方式
GB/T 7714		 Zhao, Jinyuan,Shi, Cunzhao,Jia, Fuxi,et al. Document image binarization with cascaded generators of conditional generative adversarial networks[J]. PATTERN RECOGNITION,2019,96:12.
APA Zhao, Jinyuan,Shi, Cunzhao,Jia, Fuxi,Wang, Yanna,&Xiao, Baihua.(2019).Document image binarization with cascaded generators of conditional generative adversarial networks.PATTERN RECOGNITION,96,12.
MLA Zhao, Jinyuan,et al."Document image binarization with cascaded generators of conditional generative adversarial networks".PATTERN RECOGNITION 96(2019):12.

入库方式： OAI收割

来源：自动化研究所

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