Abstract
Now a days recognizing the handwritten character is receiving high significance because of numerous applications like Educational Software, On-line Signature Verification, Bank Cheque Processing, postal code recognition, Electronic library etc. Very less work is accounted in the research of Devanagari handwritten character recognition (HWDCR), so that there is a large scope of research in this area. In this paper we proposed a HWDCR system that recognizes Devanagari handwritten characters, the most popular script in India. Using pen tablet handwritten character is inputted and its on-line features are extracted like sequence of (x, y) coordinates, stroke and pressure information which are passed to classifier for classification. We have used MLP-BP Neural Network Classifier for classification. The average recognition accuracy is achieved by the proposed HWDCR system is 90% using on-line data.
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Deore, S.P., Pravin, A. (2019). On-Line Devanagari Handwritten Character Recognition Using Moments Features. In: Santosh, K., Hegadi, R. (eds) Recent Trends in Image Processing and Pattern Recognition. RTIP2R 2018. Communications in Computer and Information Science, vol 1037. Springer, Singapore. https://doi.org/10.1007/978-981-13-9187-3_4
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DOI: https://doi.org/10.1007/978-981-13-9187-3_4
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