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Proceedings Paper

Classification of pen gestures using learning vector quantization
Author(s): Ravi V. Shankar; Dilip Krishnaswamy
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Paper Abstract

This paper deals with the classification of pen gestures using the learning vector quantization algorithm, a supervised learning technique. Both single stroke and multi stroke gestures are considered. The slope information from the strokes is extensively preprocessed before classification. The preprocessing and the classification algorithms chosen help to obtain very high rates of gesture classification. This is especially true in the multi stroke case. The recognition of the pen gestures is independent of their position, orientation, and size.

Paper Details

Date Published: 29 October 1993
PDF: 6 pages
Proc. SPIE 2032, Neural and Stochastic Methods in Image and Signal Processing II, (29 October 1993); doi: 10.1117/12.162030
Show Author Affiliations
Ravi V. Shankar, Syracuse Univ. (United States)
Dilip Krishnaswamy, Syracuse Univ. (United States)

Published in SPIE Proceedings Vol. 2032:
Neural and Stochastic Methods in Image and Signal Processing II
Su-Shing Chen, Editor(s)

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