Paper
29 October 1993 Classification of pen gestures using learning vector quantization
Ravi V. Shankar, Dilip Krishnaswamy
Author Affiliations +
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.
© (1993) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Ravi V. Shankar and Dilip Krishnaswamy "Classification of pen gestures using learning vector quantization", Proc. SPIE 2032, Neural and Stochastic Methods in Image and Signal Processing II, (29 October 1993); https://doi.org/10.1117/12.162030
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Cited by 1 scholarly publication.
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KEYWORDS
Quantization

Detection and tracking algorithms

Machine learning

Distance measurement

Neural networks

Vector spaces

Feature extraction

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