Considering the importance of handwritten documents in everyday transaction technologies like optical character recognition will be a valuable addition to the new set of technologies. This technology allows the translation of different documents and images into editable, analyzable, and searchable information. Researchers have successfully integrated technologies like machine learning and artificial intelligence to automatically analyze printed or handwritten documents for converting them into electronic formats. At the time of recognizing a text, one needs to process the input image, extraction functionality, and classification schemes. This is the training stage of the system for acknowledging specific text. In this phase, the system is trained to find out similarities and differences between handwritten sample documents. Technology makes use of images of hand transcription and then transforms these images into a digital copy. The primary aim of this research report is to understand and explain the procedure for the development of character recognition systems. It will give further direction to the technology for identifying research documents. The systematic literature review includes evaluated, collected, and synthesized articles on this technology. Most of these research articles were published between 2019 and 2021. For this research report, various electronic databases were evaluated to understand the predefined review protocol. Previously published articles were searched with the help of keywords. After a comprehensive selection process around 20 articles were shortlisted on this. This review report aims at presenting the current state of results and methodologies of OCR and also provides a new dimension in the research process. It also helps in addressing the literature gaps.
|Number of pages||11|
|Journal||Asian Journal of Social Science and Management Technology|
|Publication status||Published - Nov 2021|