• VAIBHAV VIKAS MAINKAR
• JYOTI ARJUN KATKAR
• POONAM RAJESH PEDNEKAR
• AJINKYA BHASKAR UPADE
• GAURANG DILIP VAIDYA

Character recognition for read the text from image which is the huge area for research to develop computer-based application. Nowadays, there is a storing of information from handwritten documents to computer readable format for future use. One of the simple ways to store the information from paper document is to first capture or scan the paper document and save them as an image. ‘Optical character recognition’ it is the method to transform handwritten data into electronic format. The main challenge is to recognize the character of different people having different style of handwriting. Thus, we will design a system that recognize the handwritten character from old documents. To train the neural network it become easier because availability of huge amount of data and various algorithm which are taking place. In our system we will use of OpenCV for performing image processing and will use TensorFlow for training the neural network.

Neural Network, OpenCV, TensorFlow

"Handwritten Character Recognition", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.871-874, June 2019, Available :http://www.jetir.org/papers/JETIR1907N21.pdf

"Handwritten Character Recognition", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp871-874, June 2019, Available at : http://www.jetir.org/papers/JETIR1907N21.pdf