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Ground-truthed dataset of chemical structure images in Japanese published patent applications

Authors:

Koji Nakagawa,

Akio Fujiyoshi,

Masakazu SuzukiAuthors Info & Claims

DAS '10: Proceedings of the 9th IAPR International Workshop on Document Analysis Systems

Pages 455 - 462

https://doi.org/10.1145/1815330.1815389

Published: 09 June 2010 Publication History

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Abstract

This paper presents a ground-truthed dataset of chemical structure images in Japanese published patent applications. The ground-truthed dataset of 5576 chemical images was made in the following manner. First, the graphical structure of chemical images was recognized by a chemical structure recognition software program developed by our group. Then, with a newly developed correction GUI, the graphical structure dataset was corrected manually. Second, the graphical structure dataset was converted into another dataset representing the chemical structure. The chemical structure dataset was also corrected manually by another newly developed correction GUI. The result of statistical analysis of chemical structure images contained in the Japanese published patent applications is also presented in this paper. Although we concentrated on Japanese published patent applications, this dataset includes a wide range of chemical structure images.

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Hormazabal RPark CLee SHan SJo YLee JJo AKim SChoo JLee MLee HKoyejo SMohamed SAgarwal ABelgrave DCho KOh A(2022)CEDeProceedings of the 36th International Conference on Neural Information Processing Systems10.5555/3600270.3602236(27114-27126)Online publication date: 28-Nov-2022
https://dl.acm.org/doi/10.5555/3600270.3602236
Journet NVisani MMansencal BVan-Cuong KBilly A(2017)DocCreator: A New Software for Creating Synthetic Ground-Truthed Document ImagesJournal of Imaging10.3390/jimaging30400623:4(62)Online publication date: 11-Dec-2017
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Heras LTerrades ORobles SSánchez G(2015)CVC-FP and SGTInternational Journal on Document Analysis and Recognition10.1007/s10032-014-0236-518:1(15-30)Online publication date: 1-Mar-2015
https://dl.acm.org/doi/10.1007/s10032-014-0236-5
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Published In

DAS '10: Proceedings of the 9th IAPR International Workshop on Document Analysis Systems

June 2010

490 pages

ISBN:9781605587738

DOI:10.1145/1815330

General Chairs:
David Doermann
University of Maryland, College Park
,
Venu Govindaraju
University at Buffalo, SUNY
,
Daniel Lopresti
Lehigh University
,
Prem Natarajan
Raytheon BBN Technologies

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

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Published: 09 June 2010

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DAS '10: The Eighth IAPR International Workshop on Document Analysis Systems

June 9 - 11, 2010

Massachusetts, Boston, USA

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Hormazabal RPark CLee SHan SJo YLee JJo AKim SChoo JLee MLee HKoyejo SMohamed SAgarwal ABelgrave DCho KOh A(2022)CEDeProceedings of the 36th International Conference on Neural Information Processing Systems10.5555/3600270.3602236(27114-27126)Online publication date: 28-Nov-2022
https://dl.acm.org/doi/10.5555/3600270.3602236
Journet NVisani MMansencal BVan-Cuong KBilly A(2017)DocCreator: A New Software for Creating Synthetic Ground-Truthed Document ImagesJournal of Imaging10.3390/jimaging30400623:4(62)Online publication date: 11-Dec-2017
https://doi.org/10.3390/jimaging3040062
Heras LTerrades ORobles SSánchez G(2015)CVC-FP and SGTInternational Journal on Document Analysis and Recognition10.1007/s10032-014-0236-518:1(15-30)Online publication date: 1-Mar-2015
https://dl.acm.org/doi/10.1007/s10032-014-0236-5
Frasconi PGabbrielli FLippi MMarinai S(2014)Markov Logic Networks for Optical Chemical Structure RecognitionJournal of Chemical Information and Modeling10.1021/ci500219754:8(2380-2390)Online publication date: 6-Aug-2014
https://doi.org/10.1021/ci5002197
Marinai SQuiriconi SConcolato CSchmitz P(2012)Displaying chemical structural formulae in ePub formatProceedings of the 2012 ACM symposium on Document engineering10.1145/2361354.2361382(125-128)Online publication date: 4-Sep-2012
https://dl.acm.org/doi/10.1145/2361354.2361382

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Handwritten Chemical Structure Image to Structure-Specific Markup Using Random Conditional Guided Decoder

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