![]() In the 1990s, when digitizing historical newspapers, OCR technology became prominent. ![]() Prior to the invention of optical character reader technologies, the only way to digitize handwritten paper documents was to manually retype the text. OCR processing employs a mix of hardware and software to turn paper documents into machine-readable text. It allows a large range of paper-based documents in a variety of languages and formats to be digitized into machine-readable text and improves information accessibility for users. OCR technology aids in the automation of data extraction from typed or written text in a scanned document or image file and then translating the text into a machine-readable format for data processing such as editing or searching. This process can help make the text more accessible and searchable, and it can also help preserve the original formatting of the text. OCR can be used to help digitize text from old books, documents, and other sources. Optical character recognition (OCR) is a method of converting images of typed, handwritten, or printed text into machine-encoded text. In this article, we will define optical character recognition, discuss its importance, advantages, usage, and speculate on its potential. This can help speed up the process of digitization and make it easier to search through the document later on. OCR software can be utilized to scan physical documents and convert them into digital files. ![]() OCR is typically used in businesses with large volumes of paper documents such as insurance companies, banks, libraries and government agencies. The resulting data can be used in a variety of ways, including for example, searching for words and phrases in large amounts of scanned documents or creating digital copies from printed pages. The process typically involves the use of an optical scanner, which scans the image and converts it to digital data. Optical character recognition (OCR) is a computer-based technology that converts images of text into text. OCR is typically used in business applications to capture structured information from documents and convert it into digital format for archiving, storage, and retrieval. In this digital world, optical character recognition has become an essential element in any organization digitization initiatives.
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