On-Line and Off-Line Handwriting Recognition: A Comprehensive Survey
IEEE Transactions on Pattern Analysis and Machine Intelligence
The shape of handwritten characters
Pattern Recognition Letters
ICDAR '99 Proceedings of the Fifth International Conference on Document Analysis and Recognition
Combining Online and Offline Handwriting Recognition
ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 2
Model-Based On-Line Handwritten Digit Recognition
ICPR '98 Proceedings of the 14th International Conference on Pattern Recognition-Volume 2 - Volume 2
Online Handwriting Recognition for Tamil
IWFHR '04 Proceedings of the Ninth International Workshop on Frontiers in Handwriting Recognition
Recognition-directed recovering of temporal information from handwriting images
Pattern Recognition Letters
Optimal zoning design by genetic algorithms
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Database generation and recognition of online handwritten Bangla characters
Proceedings of the International Workshop on Multilingual OCR
Attention-Feedback Based Robust Segmentation of Online Handwritten Isolated Tamil Words
ACM Transactions on Asian Language Information Processing (TALIP)
Language models for online handwritten Tamil word recognition
Proceeding of the workshop on Document Analysis and Recognition
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The spatiostructural features proposed for recognition of online handwritten characters refer to offline-like features that convey information about both the positional and structural (shape) characteristics of the handwriting unit. This paper demonstrates the effectiveness of representing an online handwritten stroke using spatiostructural features, as indicated by its effect on the stroke classification accuracy by a Support Vector Machine (SVM) based classifier. The study has been done on two major Indian writing systems, Devanagari and Tamil. The importance of localization information of the structural features and handling of translational variance is studied using appropriate approaches to zoning the handwritten character.