Simulation and Modeling of Handwritten Meitei Mayek Digits using Neural Network Approach
Author(s) : A.SURESH SINGH, ANGOM UMAKANTA SINGH, H.JAMES, N.CHANDRAKUMAR SINGH, ROMESH LAISHRAM
Abstract
Handwriting recognition is one of the most challenging research areas during last few decades. It is often useful to have machine perform pattern recognition, than the human beings. Many research works has been carried out in handwritten recognition of different Indian languages. This paper describes simulation and modeling of handwritten Meitei Mayek (Manipuri script) digit recognition (HMMDR) using a neural network approach. We have collected 1000 samples of handwritten Meitei Mayek digits from various persons. Various pre-processing steps are applied on collected sample images before passing it to the neural network. Then the Neural Network has been trained and tested on these samples.
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