Handwritten Text to Editable Text Document

  • Ankur Garg ,Payal Deora ,D.Malathi


One of the major problem faced by every organization is management of old records of handwritten text that  are likely to be subjected  to further deterioration in the future. These old records are difficult to manage  because of the sheer volume they exist in. This issue can be rectified if there existed a softcopy of those records but the Analysis of Handwritten text has been one of the major challenge in the field of image processing because of various writing styles, background lighting and text orientation. All the existing technique  have  failed when the letters in a text cannot  be segmented  properly. In  our project, the  text  will be segmented   and   then   segmented   letters  will  be  analysed   and classified into appropriate class using a neural network .With the aid of Natural Language  processing, we can analyse the context of a misclassified word and predict its occurrence in reference to the context.   With   a  proper  blend   of  image   processing,   Natural language  processing and Convolutional Neural Network, we will recognize the text with a high degree of accuracy.

How to Cite
Ankur Garg ,Payal Deora ,D.Malathi. (2020). Handwritten Text to Editable Text Document. International Journal of Advanced Science and Technology, 29(2), 4707 - 4712. Retrieved from http://sersc.org/journals/index.php/IJAST/article/view/28474