Prototype Learning Methods for Online Handwriting Recognition
ICDAR '05 Proceedings of the Eighth International Conference on Document Analysis and Recognition
Dynamic TimeWarping Applied to Tamil Character Recognitio
ICDAR '05 Proceedings of the Eighth International Conference on Document Analysis and Recognition
Machine Recognition of Online Handwritten Devanagari Characters
ICDAR '05 Proceedings of the Eighth International Conference on Document Analysis and Recognition
LipiTk: a generic toolkit for online handwriting recognition
ACM SIGGRAPH 2007 courses
Database generation and recognition of online handwritten Bangla characters
Proceedings of the International Workshop on Multilingual OCR
Divide and conquer technique in online handwritten Kannada character recognition
Proceedings of the International Workshop on Multilingual OCR
Resolving Ambiguities in Confused Online Tamil Characters with Post Processing Algorithms
PReMI '09 Proceedings of the 3rd International Conference on Pattern Recognition and Machine Intelligence
On-line Hindi handwritten character recognition for mobile devices
Proceedings of the International Conference on Advances in Computing, Communications and Informatics
Attention-Feedback Based Robust Segmentation of Online Handwritten Isolated Tamil Words
ACM Transactions on Asian Language Information Processing (TALIP)
Hindi handwritten word recognition using HMM and symbol tree
Proceeding of the workshop on Document Analysis and Recognition
Language models for online handwritten Tamil word recognition
Proceeding of the workshop on Document Analysis and Recognition
Lightweight user-adaptive handwriting recognizer for resource constrained handheld devices
Proceeding of the workshop on Document Analysis and Recognition
Levenshtein distance metric based holistic handwritten word recognition
Proceedings of the 4th International Workshop on Multilingual OCR
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We present a comparison of elastic matching schemes for writer dependent on-line handwriting recognition of isolated Tamil characters. Three different features are considered namely, preprocessed x-y co-ordinates, quantized slope values, and dominant point co-ordinates. Seven schemes based on these three features and dynamic time warping distance measure are compared with respect to recognition accuracy, recognition speed, and number of training templates. Along with these results, possible grouping strategies and error analysis is also presented in brief.