Digitizing Handwriting with a Sensor Pen: A Writer-Independent Recognizer

Wehbi M, Hamann T, Barth J, Eskofier B (2020)

Publication Type: Conference contribution

Publication year: 2020

Event location: Dortmund DE

ISBN: 9781728199665

DOI: 10.1109/ICFHR2020.2020.00061

Abstract

Online handwriting recognition has been studied for a long time with only few practicable results when writing on normal paper. Previous approaches using sensor-based devices encountered problems that limited the usage of the developed systems in real-world applications. This paper presents a writer-independent system that recognizes characters written on plain paper with the use of a sensor-equipped pen. This system is applicable in real-world applications and requires no user-specific training for recognition. The pen provides linear acceleration, angular velocity, magnetic field, and force applied by the user, and acts as a digitizer that transforms the analogue signals of the sensors into timeseries data while writing on regular paper. The dataset we collected with this pen consists of Latin lower-case and upper-case alphabets. We present the results of a convolutional neural network model for letter classification and show that this approach is practical and achieves promising results for writer-independent character recognition. This work aims at providing a realtime handwriting recognition system to be used for writing on normal paper.

Authors with CRIS profile

Mohamad Wehbi Machine Learning and Data Analytics Lab Björn Eskofier Machine Learning and Data Analytics Lab

Related research project(s)

Development of neural networks and machine learning algorithms for online handwriting recognition (EINNS) Development of neural networks and machine learning algorithms for online handwriting recognition Sept. 2, 2019 - April 30, 2022

Involved external institutions

STABILO International GmbH DE Germany (DE)

How to cite

APA:

Wehbi, M., Hamann, T., Barth, J., & Eskofier, B. (2020). Digitizing Handwriting with a Sensor Pen: A Writer-Independent Recognizer. In IEEE (Eds.), Proceedings of the 17th International Conference on Frontiers in Handwriting Recognition (ICFHR). Dortmund, DE.

MLA:

Wehbi, Mohamad, et al. "Digitizing Handwriting with a Sensor Pen: A Writer-Independent Recognizer." Proceedings of the 17th International Conference on Frontiers in Handwriting Recognition (ICFHR), Dortmund Ed. IEEE, 2020.

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