Advanced Automated Document Processing Using Optical Character Recognition (OCR)
This research paper delves into the exploration of OCR technologies aimed at addressing the inherent challenges associated with recognizing handwritten text and investigates pre-processing techniques to enhance the accuracy of character prediction.
Abstract
In contemporary times, there is an exponential surge in the volume of handwritten and scanned documents. The manual entry of information into systems is not only impractical but also time-consuming. Handwritten forms are extensively utilized in various sectors, including the banking industry for transactional purposes and numerous educational institutions for admission and other applications. In response to this challenge, we propose a solution involving the development of a model utilizing Optical Character Recognition (OCR) technology to efficiently extract text from scanned documents.This research paper delves into the exploration of OCR technologies aimed at addressing the inherent challenges associated with recognizing handwritten text. Furthermore, the study investigates pre-processing techniques to enhance the accuracy of character prediction. Through the integration of these advanced technologies, our objective is to create a more efficient and precise automated document processing system, thereby minimizing manual intervention and elevating overall productivity.