NAOC Open IR
Intelligent Recognition of Time Stamp Characters in Solar Scanned Images from Film
Zhang, Jiafeng1; Lin, Guangzhong1; Zeng, Shuguang1; Zheng, Sheng1; Yang, Xiao2; Lin, Ganghua2; Zeng, Xiangyun1; Wang, Haimin3
2019-08-28
Source PublicationADVANCES IN ASTRONOMY
ISSN1687-7969
Volume2019Pages:9
AbstractPrior to the availability of digital cameras, the solar observational images are typically recorded on films, and the information such as date and time were stamped in the same frames on film. It is significant to extract the time stamp information on the film so that the researchers can efficiently use the image data. This paper introduces an intelligent method for extracting time stamp information, namely, the convolutional neural network (CNN), which is an algorithm in deep learning of multilayer neural network structures and can identify time stamp character in the scanned solar images. We carry out the time stamp decoding for the digitized data from the National Solar Observatory from 1963 to 2003. The experimental results show that the method is accurate and quick for this application. We finish the time stamp information extraction for more than 7 million images with the accuracy of 98%.
Funding OrganizationNational Natural Science Foundation of China ; National Natural Science Foundation of China ; 13th Five-year Informatization Plan of Chinese Academy of Sciences ; 13th Five-year Informatization Plan of Chinese Academy of Sciences ; Beijing Municipal Science and Technology Project ; Beijing Municipal Science and Technology Project ; US NSF ; US NSF ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; 13th Five-year Informatization Plan of Chinese Academy of Sciences ; 13th Five-year Informatization Plan of Chinese Academy of Sciences ; Beijing Municipal Science and Technology Project ; Beijing Municipal Science and Technology Project ; US NSF ; US NSF ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; 13th Five-year Informatization Plan of Chinese Academy of Sciences ; 13th Five-year Informatization Plan of Chinese Academy of Sciences ; Beijing Municipal Science and Technology Project ; Beijing Municipal Science and Technology Project ; US NSF ; US NSF ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; 13th Five-year Informatization Plan of Chinese Academy of Sciences ; 13th Five-year Informatization Plan of Chinese Academy of Sciences ; Beijing Municipal Science and Technology Project ; Beijing Municipal Science and Technology Project ; US NSF ; US NSF
DOI10.1155/2019/6565379
WOS KeywordNEURAL-NETWORKS ; DEEP
Language英语
Funding ProjectNational Natural Science Foundation of China[U1731124] ; National Natural Science Foundation of China[U1531247] ; National Natural Science Foundation of China[11427803] ; National Natural Science Foundation of China[11427901] ; National Natural Science Foundation of China[11873062] ; 13th Five-year Informatization Plan of Chinese Academy of Sciences[XXH13505-04] ; Beijing Municipal Science and Technology Project[Z181100002918004] ; US NSF[AGS-1620875]
Funding OrganizationNational Natural Science Foundation of China ; National Natural Science Foundation of China ; 13th Five-year Informatization Plan of Chinese Academy of Sciences ; 13th Five-year Informatization Plan of Chinese Academy of Sciences ; Beijing Municipal Science and Technology Project ; Beijing Municipal Science and Technology Project ; US NSF ; US NSF ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; 13th Five-year Informatization Plan of Chinese Academy of Sciences ; 13th Five-year Informatization Plan of Chinese Academy of Sciences ; Beijing Municipal Science and Technology Project ; Beijing Municipal Science and Technology Project ; US NSF ; US NSF ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; 13th Five-year Informatization Plan of Chinese Academy of Sciences ; 13th Five-year Informatization Plan of Chinese Academy of Sciences ; Beijing Municipal Science and Technology Project ; Beijing Municipal Science and Technology Project ; US NSF ; US NSF ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; 13th Five-year Informatization Plan of Chinese Academy of Sciences ; 13th Five-year Informatization Plan of Chinese Academy of Sciences ; Beijing Municipal Science and Technology Project ; Beijing Municipal Science and Technology Project ; US NSF ; US NSF
WOS Research AreaAstronomy & Astrophysics
WOS SubjectAstronomy & Astrophysics
WOS IDWOS:000486022100001
PublisherHINDAWI LTD
Citation statistics
Document Type期刊论文
Identifierhttp://ir.bao.ac.cn/handle/114a11/27750
Collection中国科学院国家天文台
Corresponding AuthorZeng, Shuguang
Affiliation1.China Three Gorges Univ, Coll Sci, Yichang 443002, Peoples R China
2.Chinese Acad Sci, Natl Astron Observ, Key Lab Solar Act, Beijing 100101, Peoples R China
3.New Jersey Inst Technol, Inst Space Weather Sci, 323 Martin Luther King Blvd, Newark, NJ 07102 USA
Recommended Citation
GB/T 7714
Zhang, Jiafeng,Lin, Guangzhong,Zeng, Shuguang,et al. Intelligent Recognition of Time Stamp Characters in Solar Scanned Images from Film[J]. ADVANCES IN ASTRONOMY,2019,2019:9.
APA Zhang, Jiafeng.,Lin, Guangzhong.,Zeng, Shuguang.,Zheng, Sheng.,Yang, Xiao.,...&Wang, Haimin.(2019).Intelligent Recognition of Time Stamp Characters in Solar Scanned Images from Film.ADVANCES IN ASTRONOMY,2019,9.
MLA Zhang, Jiafeng,et al."Intelligent Recognition of Time Stamp Characters in Solar Scanned Images from Film".ADVANCES IN ASTRONOMY 2019(2019):9.
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