In the present work, a new feature vector has been designed towards recognition of handwritten online Bangla basic characters. At first, Center of Gravity (CG) of a particular character sample is determined. After that a circle enclosing the character sample is drawn whose radius is estimated as the distance of farthest data pixel from that CG. From this circular region, a 136-element feature vector is generated considering both the global as well as local information of the character sample. The feature set has been tested with several well-known classifiers on 10, 000 isolated Bangla basic characters. Finally, Support Vector Machine (SVM) has produced 98.26% recognition accuracy.
CITATION STYLE
Sen, S., Bhattacharyya, A., Das, A., Sarkar, R., & Roy, K. (2017). Design of novel feature vector for recognition of online handwritten bangla basic characters. In Advances in Intelligent Systems and Computing (Vol. 458, pp. 485–494). Springer Verlag. https://doi.org/10.1007/978-981-10-2035-3_50
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