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Content Provider | IEEE Xplore Digital Library |
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Author | Fink, G.A. Wienecke, M. Sagerer, G. |
Copyright Year | 2001 |
Description | Author affiliation: Fac. of Technol., Bielefeld Univ., Germany (Fink, G.A.) |
Abstract | The use of handwriting provides a natural way of interacting with small portable computers. However, in order to capture handwritten text. online, special input devices are necessary. Therefore, M.E. Munich & P. Perona (1996) proposed to use visual input for pen-based computers. Writing can then be performed on ordinary paper, and pen trajectories are automatically extracted from image sequences recorded during the writing process. On the basis of this work, we developed a complete video-based online handwriting recognition system. We will present the techniques applied for pen tracking, pre-processing, feature extraction, and statistical modeling and recognition. Evaluation results on a writer-independent unconstrained handwriting recognition task demonstrate that the inherent limitations of the video-based approach can be compensated using robust modeling combined with adaptation techniques. |
Sponsorship | IAPR |
Starting Page | 226 |
Ending Page | 230 |
File Size | 637767 |
Page Count | 5 |
File Format | |
ISBN | 0769512631 |
DOI | 10.1109/ICDAR.2001.953788 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2001-09-13 |
Publisher Place | USA |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Handwriting recognition Writing Image sequences Spatial resolution Portable computers Robustness Cameras Feature extraction Adaptation model Personal digital assistants |
Content Type | Text |
Resource Type | Article |
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