Paper Title
Handwriting Character Recognition using Neural Network

Abstract
Handwriting character recognition remains largely unsolve problems due to the presence of many handwritten characters present around the world. There are many existing advance methods which do not lead to a proper solution for handwriting character recognition. In this research paper we will designate the following proposal to get maximum accuracy (90%) in the field of handwriting character recognition. The handwriting character recognition will be done by using pytesseract, convutional neural network and tensor flow. When handwritten texts or scripts are automatically identifies by a system, it helps in providing many necessary applications globally such as multilingual document's transcription and even the documents can be searches on the internet that contains various distinct scripts. there are many handheld devices available that captures and scan handwritten inputs, and due to their popularity in the market different algorithms has been creates that can easily do the analysis and yield the result in no time. Keywords - Handwriting Character Recognition, Neural Network, PyTesseract, Python openCV, Tensor Flow.

Author - Sanil Jain, Rahul Tiwari, Rishabh Soni

Published : Volume-7,Issue-8  ( Aug, 2020 )

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