Optical Character Recognition (OCR) is the process of extracting and converting handwritten or typed text from images, videos, or scanned documents (such as PDFs) into a digitally editable format (like TXT or DOCX). This technology is a branch of artificial intelligence closely related to computer vision and pattern recognition. OCR enables the encoding of printed text from images, making it possible to electronically modify, search, and store the information more compactly. It also allows this information to be presented online and utilized in machine processes, including cognitive computing. The applications of OCR span a wide range, from personal use to public security. Furthermore, OCR technology has revolutionized the way we digitize and manage documents. Its capabilities include: * Scanned Document Recognition: Printed documents are scanned, and OCR software converts them into searchable and editable text. This enables users to extract information from old documents and incorporate it into modern workflows. It is commonly used to automate the processing of legal documents and extract data from bank statements and invoices, streamlining tasks like invoice processing and financial record keeping. * Scene Text Recognition: OCR can identify text in natural scenes, such as street signs, storefronts, or license plates. It performs well under various conditions, including low light or blurry images, making it useful for recognizing text in street art or images captured by drones. * Intelligent Character Recognition (ICR): This feature allows OCR systems to recognize and transcribe handwritten or cursive text from scanned documents, facilitating the digitization of handwritten notes, letters, and forms. ICR specifically focuses on transcribing cursive and script handwriting.
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