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Data-embedding pen: augmenting ink strokes with meta-information

Published: 09 June 2010 Publication History

Abstract

In this paper we present the first operational version of the data-embedding pen. During writing a pattern, this pen produces an additional ink-dot sequence along the ink stroke of the pattern. The ink-dot sequence represents, for example, meta-information (such as the writer's name and the date of writing) and thus drastically increases the value of the handwriting on a physical paper. Since the information is placed on the paper, it can be extracted just by scanning or photographing the paper. There is no need to get access to any memory on the pen to recover the information. This is useful especially in multi-writer or multi-pen scenarios. The experiments using an encoding scheme and a decoding algorithm showed very promising results. For example, it was proved that we can embed 28 or more bits of information on simple handwritten patterns and decode them with a high reliability.

References

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E.-M. Nel, J. A. du Preez, and B. M. Herbst. Estimating the pen trajectories of static signatures using hidden markov models. IEEE Trans. Pat. Anal. Mach. Intell., 27(11):1733--1746, 2005.
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S. Uchida, K. Tanaka, M. Iwamura, S. Omachi, and K. Kise. A Data-Embedding Pen. In Tenth International Workshop on Frontiers in Handwriting Recognition, 2006.
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Cited By

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  • (2018)Pen Tip Motion Prediction for Handwriting Drawing Order Recovery using Deep Neural Network2018 24th International Conference on Pattern Recognition (ICPR)10.1109/ICPR.2018.8546086(704-709)Online publication date: Aug-2018
  • (2015)Data Embedding into CharactersIEICE Transactions on Information and Systems10.1587/transinf.2014MUI0002E98.D:1(10-20)Online publication date: 2015
  • (2014)More than ink - Realization of a data-embedding penPattern Recognition Letters10.1016/j.patrec.2012.09.00135(246-255)Online publication date: 1-Jan-2014
  • Show More Cited By

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cover image ACM Other conferences
DAS '10: Proceedings of the 9th IAPR International Workshop on Document Analysis Systems
June 2010
490 pages
ISBN:9781605587738
DOI:10.1145/1815330
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

New York, NY, United States

Publication History

Published: 09 June 2010

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View all
  • (2018)Pen Tip Motion Prediction for Handwriting Drawing Order Recovery using Deep Neural Network2018 24th International Conference on Pattern Recognition (ICPR)10.1109/ICPR.2018.8546086(704-709)Online publication date: Aug-2018
  • (2015)Data Embedding into CharactersIEICE Transactions on Information and Systems10.1587/transinf.2014MUI0002E98.D:1(10-20)Online publication date: 2015
  • (2014)More than ink - Realization of a data-embedding penPattern Recognition Letters10.1016/j.patrec.2012.09.00135(246-255)Online publication date: 1-Jan-2014
  • (2013)Data-Embedding PenMultimedia Information Hiding Technologies and Methodologies for Controlling Data10.4018/978-1-4666-2217-3.ch018(396-411)Online publication date: 2013

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