Abstract
Dataset development is one of the most imperative tasks in document image processing research. The problem becomes more challenging when it comes about Numeral Image Database (NIdb) for official Indic scripts. Few efforts are made so far but they were restricted on single script which is basically a local script of the fellow researcher who prepared the database. In this paper, a technique for development of a handwritten NIdb of four popular Indic scripts namely Bangla, Devanagari, Roman and Urdu is proposed. Initially data were collected in unconstrained manner at Word-level from different writers with varying age, sex and educational qualification. All the images are stored in grey-level at .jpg format so that the data can be used in various ways as per need. A benchmark result on the present dataset is proposed using a novel hybrid approach with respect to Handwritten Numeral Script Identification (HNSI) problem.
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Acknowledgement
The authors are very much thankful to Mr. Tousif Jaman and Mr. Sahaniaj Dhukra, students of Aliah University for their immense help during data collection process.
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Obaidullah, S.M., Halder, C., Das, N., Roy, K. (2016). A Corpus of Word-Level Offline Handwritten Numeral Images from Official Indic Scripts. In: Satapathy, S., Raju, K., Mandal, J., Bhateja, V. (eds) Proceedings of the Second International Conference on Computer and Communication Technologies. Advances in Intelligent Systems and Computing, vol 379. Springer, New Delhi. https://doi.org/10.1007/978-81-322-2517-1_67
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DOI: https://doi.org/10.1007/978-81-322-2517-1_67
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