A Framework for Adaptation of the Active-DTW Classifier for Online Handwritten Character Recognition

: © A Framework for Adaptation of the Active-DTW Classifier for Online Handwritten Character Recognition Vandana Roy, Sriganesh Madhvanath, Anand S., Raghunath R. Sharma HP Laboratories HPL-2009-329 online handwritten character recognition, classifier, adaptation, Active-DTW Practical applications of online handwritten character recognition demand robust and highly accurate recognition along with low memory requirements. The Active-DTW [11] classifier proposed by Sridhar et al. combines the advantages of generative and discriminative classifiers to address the similarity of between-class samples, while taking into account the variability of writing styles within the same character class. Active-DTW uses Active Shape Models to model the significant writing styles in a memory efficient manner. However, in order to create accurate models, a large number of training samples is needed up front, which is not desirable or available in many practical applications. In this paper, we propose a ...

• Type: Conference
• Year: 2009
• Where: ICDAR
• Authors: Vandana Roy, Sriganesh Madhvanath, Anand S., Ragunath R. Sharma
• Keywords: Active-dtw Classifier, Document Analysis, Handwritten Character Recognition, ICDAR 2009, Online Handwritten Character