The State of the Art in Online Handwriting Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
On-Line and Off-Line Handwriting Recognition: A Comprehensive Survey
IEEE Transactions on Pattern Analysis and Machine Intelligence
The IRESTE On/Off (IRONOFF) Dual Handwriting Database
ICDAR '99 Proceedings of the Fifth International Conference on Document Analysis and Recognition
Principal Component Analysis for Online Handwritten Character Recognition
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 2 - Volume 02
Representation and Annotation of Online Handwritten Data
IWFHR '04 Proceedings of the Ninth International Workshop on Frontiers in Handwriting Recognition
Comparison of Elastic Matching Algorithms for Online Tamil Handwritten Character Recognition
IWFHR '04 Proceedings of the Ninth International Workshop on Frontiers in Handwriting Recognition
UPX: A New XML Representation for Annotated Datasets of Online Handwriting Data
ICDAR '05 Proceedings of the Eighth International Conference on Document Analysis and Recognition
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This paper describes Lipi Toolkit (LipiTk) - a generic toolkit whose aim is to facilitate development of online handwriting recognition engines for new scripts, and simplify integration of the resulting engines into real-world application contexts. The toolkit provides robust implementations of tools, algorithms, scripts and sample code necessary to support the activities of handwriting data collection and annotation, training and evaluation of recognizers, packaging of engines and their integration into pen-based applications. The toolkit is designed to be extended with new tools and algorithms to meet the requirements of specific scripts and applications. The toolkit attempts to satisfy the requirements of a diverse set of users, such as researchers, commercial technology providers, do-it-yourself enthusiasts and application developers. In this paper we describe the first version of the toolkit which focuses on isolated online handwritten shape and character recognition.