CASIA OpenIR  > 模式识别国家重点实验室  > 先进时空数据分析与学习
Baselines Extraction from Curved Document Images via Slope Fields Recovery
Meng, Gaofeng1; Pan, Chunhong1; Xiang, Shiming1; Wu, Ying2
Source PublicationIEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
ISSN0162-8828
2020-04-01
Volume42Issue:4Pages:793-808
Abstract

Baselines estimation is a critical preprocessing step for many tasks of document image processing and analysis. The problem is very challenging due to arbitrarily complicated page layouts and various types of image quality degradations. This paper proposes a method based on slope fields recovery for curved baseline extraction from a distorted document image captured by a hand-held camera. Our method treats the curved baselines as the solution curves of an ordinary differential equation defined on a slope field. By assuming the page shape is a smooth and developable surface, we investigate a type of intrinsic geometric constraints of baselines to estimate the latent slope field. The curved baselines are finally obtained by solving an ordinary differential equation through the Euler method. Unlike the traditional text-lines based methods, our method is free from text-lines detection and segmentation. It can exploit multiple visual cues other than horizontal text-lines available in images for baselines extraction and is quite robust to document scripts, various types of image quality degradation (e.g., image distortion, blur and non-uniform illumination), large areas of non-textual objects and complex page layouts. Extensive experiments on synthetic and real-captured document images are implemented to evaluate the performance of the proposed method.

KeywordEstimation Image segmentation Layout Distortion Strips Image quality Degradation Document image processing curved baselines extraction slope fields recovery geometric distortion rectification
DOI10.1109/TPAMI.2018.2886900
WOS KeywordTEXT ; SEGMENTATION ; RECTIFICATION ; ROBUST ; SET
Indexed BySCI
Language英语
Funding ProjectNational Natural Science Foundation of China[91646207] ; National Natural Science Foundation of China[61573352] ; National Natural Science Foundation of China[61802407] ; US National Science Foundation[IIS1217302] ; US National Science Foundation[IIS-1619078] ; Army Research Office ARO[W911NF-16-1-0138]
Funding OrganizationNational Natural Science Foundation of China ; US National Science Foundation ; Army Research Office ARO
WOS Research AreaComputer Science ; Engineering
WOS SubjectComputer Science, Artificial Intelligence ; Engineering, Electrical & Electronic
WOS IDWOS:000526541100003
PublisherIEEE COMPUTER SOC
Citation statistics
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/38831
Collection模式识别国家重点实验室_先进时空数据分析与学习
Corresponding AuthorXiang, Shiming
Affiliation1.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Zhongguancun East Rd 95, Beijing 100190, Peoples R China
2.Northwestern Univ, 2145 Sheridan Rd, Evanston, IL 60208 USA
First Author AffilicationChinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
Corresponding Author AffilicationChinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
Recommended Citation
GB/T 7714
Meng, Gaofeng,Pan, Chunhong,Xiang, Shiming,et al. Baselines Extraction from Curved Document Images via Slope Fields Recovery[J]. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE,2020,42(4):793-808.
APA Meng, Gaofeng,Pan, Chunhong,Xiang, Shiming,&Wu, Ying.(2020).Baselines Extraction from Curved Document Images via Slope Fields Recovery.IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE,42(4),793-808.
MLA Meng, Gaofeng,et al."Baselines Extraction from Curved Document Images via Slope Fields Recovery".IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE 42.4(2020):793-808.
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