Off-line cursive handwritten Tamil character recognition
WSEAS Transactions on Signal Processing
Online handwriting recognition for the Arabic letter set
CIT'11 Proceedings of the 5th WSEAS international conference on Communications and information technology
HMM-based online handwritten gurmukhi character recognition
Machine Graphics & Vision International Journal
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
Global and local features for recognition of online handwritten numerals and Tamil characters
Proceedings of the 4th International Workshop on Multilingual OCR
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Hidden Markov Models (HMM) have long been a popu- lar choice for Western cursive handwriting recognition fol- lowing their success in speech recognition. Even for the recognition of Oriental scripts such as Chinese, Japanese and Korean, Hidden Markov Models are increasingly being used to model substrokes of characters. However, when it comes to Indic script recognition, the published work em- ploying HMMs is limited, and generally focussed on iso- lated character recognition. In this effort, a data-driven HMM-based online handwritten word recognition system for Tamil, an Indic script, is proposed. The accuracies obtained ranged from 98% to 92.2% with different lexicon sizes (1K to 20K words). These initial results are promising and warrant further research in this direction. The results are also encouraging to explore possibilities for adopting the approach to other Indic scripts as well.