HMM-Based Online Handwriting Recognition System for Telugu Symbols
V. Babu, L. Prasanth, Rajiv Kumar Sharma, G.V. Rao, Anil Anthony Bharath · Proceedings of the International Conference on Document Analysis and Recognition · 2007
In this paper we present an online handwritten symbol recognition system for Telugu, a widely spoken language in India. The system is based on hidden Markov models (HMM) and uses a combination of time-domain and frequency-domain features. The system gives top-1 accuracy of 91.6% and top-5 accuracy of 98.7% on a dataset containing 29,158 train samples and 9,235 test samples. We also introduce a cost-effective and natural data collection procedure based on ACECADreg Digimemoreg and describe its usage in building a Telugu handwriting dataset.