![]() The procedure requires manual assistance and might be time-consuming and inefficient.įurthermore, digitizing this document material generates picture files that include the text contained inside them. While paperless document management is the way to go, scanning a document into an image poses challenges. These vast amounts of documentation require a significant amount of time and space to keep and handle. Some OCR systems are capable of producing annotated PDF files that include both the before and after versions of the scanned material.īusiness procedures include the use of paper forms, invoices, scanned legal documents, and printed contracts. The technology turns the extracted text data into a digital file after analysis. It then employs these characteristics to locate the best match or nearest neighbor among its many stored glyphs. This approach works effectively with scanned images of papers typed in a known font.įeature extraction decomposes or breaks down glyphs into characteristics like lines, closed loops, line direction, and line junctions. Pattern recognition is only possible if the stored glyph has the same font and scale as the input glyph. Pattern matching works by comparing a character picture, known as a glyph, to another similarly stored glyph. Pattern matching and feature extraction are the two primary types of OCR algorithms or software processes that an OCR program utilizes for text recognition.
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