Optical Character Recognition
Optical Character Recognition (OCR for short) is the overall conversion of typed or printed text into digital data. OCR can recognize text from a variety of sources; scanned documents, a photo of a document, text in a photograph, or text overlaid on a photo (such a caption). OCR works via a method called “pattern matching” where each letter appearing in an image or document is analyzed against a stored library of glyphs to determine what letter it is. Once a match is made the OCR engine can then convert the image to machine-readable data.
Intelligent Character Recognition
Intelligent Character Recognition (ICR for short) is also known as “advanced OCR” in that it can accurately analyze and convert hand-written text to machine-readable data. This gives it advantages over OCR because it is not limited to printed documents or certain fonts – in fact, its engines are constantly learning to recognize new handwriting patterns to improve its overall accuracy.
Optical Mark Recognition
Optical Mark Recognition (OMR for short) is used as a method to interpret non-text markings on a document as data. These markings can be supplied as answers to a test, votes on a ballot, or responses to a survey. The ability to recognize markings is useful for enterprises as it allows them to limit the number or type of response to a specific element of data, such as a yes/no question on an application. Once recognized, these markings can be fed into the processing system as useful business data.
Intelligent Document Recognition
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