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2019 | OriginalPaper | Chapter

DFA-Based Online Bangla Character Recognition

Authors : Shibaprasad Sen, Dwaipayan Shaoo, Mridul Mitra, Ram Sarkar, Kaushik Roy

Published in: Information Technology and Applied Mathematics

Publisher: Springer Singapore

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Abstract

In the present experiment, we have investigated the effectiveness of two handcrafted feature extraction techniques for the recognition of constituent strokes of online handwritten Bangla character samples. These techniques estimate local and global shape information from a stroke sample. Combined feature vector is fed to Multi-Layer Perceptron (MLP)-based classifier for stroke recognition purpose. We have achieved 91.27% recognition accuracy over test set. In the current experiment, total size of the stroke database is 32,534. Among the samples, 30% of the entire strokes are considered as test set and rest are used to train the recognition model. Afterward, we have implemented a Deterministic Finite Automata (DFA)-based character recognition system from the recognized strokes. Final outcome of the system is satisfactory considering the stroke variation orders while writing Bangla characters.

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Title: DFA-Based Online Bangla Character Recognition
Authors: Shibaprasad Sen
Dwaipayan Shaoo
Mridul Mitra
Ram Sarkar
Kaushik Roy
Publisher: Springer Singapore
Book: Information Technology and Applied Mathematics
Print ISBN: 978-981-10-7589-6

Electronic ISBN: 978-981-10-7590-2

Copyright Year: 2019
DOI: https://doi.org/10.1007/978-981-10-7590-2_13

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