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Schmid, Andreas ; Heckelbacher, Lorenz ; Wimmer, Raphael

Extracting Handwritten Annotations from Printed Documents Via Infrared Scanning

Schmid, Andreas , Heckelbacher, Lorenz and Wimmer, Raphael (2022) Extracting Handwritten Annotations from Printed Documents Via Infrared Scanning. In: CHI Conference on Human Factors in Computing SystemsExtended Abstracts (CHI ’22 Extended Abstracts), April 29 - May 5, 2022, New Orleans, LA, USA.

Date of publication of this fulltext: 28 Oct 2022 14:45
Conference or workshop item
DOI to cite this document: 10.5283/epub.53129


Abstract

Despite ever improving digital ink and paper solutions, many people still prefer printing out documents for close reading, proofreading, or filling out forms. However, in order to incorporate paper-based annotations into digital workflows, handwritten text and markings need to be extracted. Common computer-vision and machine-learning approaches require extensive sets of training data or a clean ...

Despite ever improving digital ink and paper solutions, many people still prefer printing out documents for close reading, proofreading, or filling out forms. However, in order to incorporate paper-based annotations into digital workflows, handwritten text and markings need to be extracted. Common computer-vision and machine-learning approaches require extensive sets of training data or a clean digital version of the document. We propose a simple method for extracting handwritten annotations from laser-printed documents using multispectral imaging. While black toner absorbs infrared light, most inks are invisible in the infrared spectrum. We modified an off-the-shelf flatbed scanner by adding a switchable infrared LED to its light guide. By subtracting an infrared scan from a color scan, handwritten text and highlighting can be extracted and added to a PDF version. Initial experiments show accurate results with high quality on a test data set of 93 annotated pages. Thus, infrared scanning seems like a promising building block for integrating paper-based and digital annotation practices.



Involved Institutions


Details

Item typeConference or workshop item (Poster)
Publisher:Association for Computing Machinery
Open Access Type:Assoc. of Comp. Machinery (ACM)
Page Range:Art. no. 363
Date29 April 2022
Additional Information (public)erschienen in: Barbosa, Simone: CHI Conference on Human Factors in Computing Systems Extended Abstracts. New York: Association for Computing Machinery, 2022, ISBN 978-1-4503-9156-6
InstitutionsLanguages and Literatures > Institut für Information und Medien, Sprache und Kultur (I:IMSK) > Lehrstuhl für Medieninformatik (Prof. Dr. Christian Wolff)
Informatics and Data Science > Department Human-Centered Computing > Lehrstuhl für Medieninformatik (Prof. Dr. Christian Wolff)

Languages and Literatures > Institut für Information und Medien, Sprache und Kultur (I:IMSK) > Lehrstuhl für Medieninformatik (Prof. Dr. Christian Wolff) > Physical-Digital Affordances (Dr. Raphael Wimmer)
Informatics and Data Science > Department Human-Centered Computing > Lehrstuhl für Medieninformatik (Prof. Dr. Christian Wolff) > Physical-Digital Affordances (Dr. Raphael Wimmer)
Informatics and Data Science > Department Human-Centered Computing > Physical-Digital Affordances (Dr. Raphael Wimmer)
Identification Number
ValueType
10.1145/3491101.3519872DOI
Related URLs
URLURL Type
https://hci.uni-regensburg.de/projects/infrared_scanProject
Keywordsannotation extraction, multispectral imaging, computer vision
Dewey Decimal Classification000 Computer science, information & general works > 004 Computer science
StatusPublished
RefereedUnknown
Created at the University of RegensburgYes
URN of the UB Regensburgurn:nbn:de:bvb:355-epub-531293
Item ID53129

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