An Approach to Identify Unique Styles in Online Handwriting Recognition
Bharath, A.; Deepu, V.; Madhvanath, Sriganesh
HPL-2005-108
External - Copyright Consideration
Keyword(s): clustering; stopping criteria; online handwriting; style identification
Abstract: 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 efficient 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.
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