Abstract
This paper deals with stroke-based online Bangla character recognition strategy. In the present work, constituent strokes have been extracted from characters and then popularly used distance based features have been estimated in order to recognize the basic strokes. Next, a rule-based approach is followed for the recognition of the characters from the previously recognized strokes. A total of 15,000 isolated online handwritten Bangla characters contributing 32,534 stroke samples have been used in this experiment, and a satisfactory result of 89.39% recognition accuracy has been achieved.
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Sen, S., Sarkar, R., Roy, K. (2017). An Approach to Stroke-Based Online Handwritten Bangla Character Recognition. In: Chaki, R., Saeed, K., Cortesi, A., Chaki, N. (eds) Advanced Computing and Systems for Security. Advances in Intelligent Systems and Computing, vol 568. Springer, Singapore. https://doi.org/10.1007/978-981-10-3391-9_10
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DOI: https://doi.org/10.1007/978-981-10-3391-9_10
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