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Eighth International Conference on Document Analysis and Recognition (ICDAR'05)
An Approach to Identify Unique Styles in Online Handwriting Recognition
Seoul, Korea
August 31-September 01
ISBN: 0-7695-2420-6
A. Bharath, Hewlett-Packard Labs India
V. Deepu, Hewlett-Packard Labs India
Sriganesh Madhvanath, Hewlett-Packard Labs India
We describe a method for identifying different writing styles of online handwritten characters based on clustering. The motivation of this experiment is to develop automatic characterization of different writing styles that arise due to variation in stroke number or stroke ordering. An ef- ficient agglomerative hierarchical clustering technique with the nearest neighbor approach was implemented to cluster strokes. The results obtained from our experiment indicate that the resulting prototypes are unique and essentially capture different writing styles.
Citation:
A. Bharath, V. Deepu, Sriganesh Madhvanath, "An Approach to Identify Unique Styles in Online Handwriting Recognition," icdar, pp.775-779, Eighth International Conference on Document Analysis and Recognition (ICDAR'05), 2005
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