Abstract
A segmentation-free approach is proposed to recognize the handwritten city names written in Bangla script. Initially, all the word images are converted into virtually single connected component following the refraction properties of light in order to design a unique shape-context of the same. Then a 64-dimensional feature vector is estimated from the said shape-context of each word image. A database containing 150 samples of 50 most popular city names of West Bengal, a state of India is prepared for evaluating the present method. Performance of this feature vector is also compared with some recently published feature vectors, and it is observed that the newly designed feature vector has outperformed the others.
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Sahoo, S., Nandi, S.K., Barua, S., Pallavi, Malakar, S., Sarkar, R. (2018). Handwritten Bangla City Name Recognition Using Shape-Context Feature. In: Bhateja, V., Coello Coello, C., Satapathy, S., Pattnaik, P. (eds) Intelligent Engineering Informatics. Advances in Intelligent Systems and Computing, vol 695. Springer, Singapore. https://doi.org/10.1007/978-981-10-7566-7_44
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DOI: https://doi.org/10.1007/978-981-10-7566-7_44
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