Abstract
In this paper, an effort has been made to emphasize the usefulness of Hausdorff Distance (HD) and Directed Hausdorff Distance (DHD) based features for the recognition of online handwritten Bangla basic characters. Every character sample is divided into N number of rectangular zones and then HD- and DHD-based features have been computed from every zone to every other zone. These distance measurements are served as feature values for the present work. Experiment has been done on a set of 10,000 character dataset. Multilayer Perceptron (MLP) produces the best result with an accuracy of 95.57% when sample character is divided into 16 rectangular zones and DHD-based procedure has been considered.
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Sen, S., Sarkar, R., Roy, K., Hori, N. (2017). Recognize Online Handwritten Bangla Characters Using Hausdorff Distance-Based Feature. In: Satapathy, S., Bhateja, V., Udgata, S., Pattnaik, P. (eds) Proceedings of the 5th International Conference on Frontiers in Intelligent Computing: Theory and Applications . Advances in Intelligent Systems and Computing, vol 515. Springer, Singapore. https://doi.org/10.1007/978-981-10-3153-3_54
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DOI: https://doi.org/10.1007/978-981-10-3153-3_54
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