Senior Citizen Social Pension Management System Using Optical Character Recognition

Abstract

Optical Character Recognition is the conversion of scanned images of handwritten or typed text to digital text. It can be beneficial for organizations for automating input of data from forms to their systems. Despite being beneficial to organizations, challenges may be faced considering that there are multiple factors that can affect the accuracy of OCR especially when it is a non OCR form. This study aims to develop a senior management system and implement handwritten OCR in one of the many programs of the local government units in the Philippines. The system was developed to decrease the use of paper and speed up the process of finding records etc. The researchers took this opportunity to implement handwritten OCR in a non-OCR form to test the accuracy of converting handwritten text to digital text. From the initial results, this study showed the possible limitations the users may face when handwritten OCR in a non-OCR form is implemented.