Handwritten Text Recognition using Deep Learning
A Nikitha, J. Geetha, D. S. Jayalakshmi
Abstract
There are many researchers working on handwritten text recognition (HTR) and also contributing to HTR domain. Even though many research methods are existing for HTR, there is a need for some more improvements in the accuracy of the HTR systems. This paper is a contribution of the application of the Deep Learning algorithm for the HTR system. In this paper first we will collect the data for training the handwritten texts, later features have been extracted from those text datasets and perform training of the model using Deep Learning approach. In this work we are going to use the strategy to recognize in terms of words rather those characters so that accuracy will be improved. The built model using LSTM deep model achieves a very good accuracy. Lastly, this developed approach of the HTR system is integrated into the OCR system and comparison of results are reported in this paper. Two approaches have been compared in this paper on IAM handwritten data set, and found that 2DLSTM based approach outperforms the other approach.