Image Capture, Image Recognition and Image Processing

Image Capture was used primarily by data entry operators who would view information on the screen to enter into a database. TAWPI has evolved and so too have the technologies used for work process improvement.

In time, images captured were able to have much of that information extracted automatically with the use of Recognition Technologies. Using recognition technologies, information is captured by a keyless method, with the computer ‘reading’ the document using sophisticated systems that identify and interpret the data. There are several types of image capture and recognition technologies. Image Capture Recognition engines offer the potential for greater productivity than either keying from images or keying from paper.

FOUR TYPES OF IMAGE CAPTURE RECOGNITION:

Barcode Recognition can be the easiest and most accurate if the bars are sufficiently spaced, because they have defined symbologies which can be self checking, character sets are defined, and many have defined check digits to ensure accurate decoding.

 

Optical Mark Recognition (OMR) is used to detect and recognize boxes, circles or ovals that are filled in by pencil. It can be very accurate when converted with a specialized reader using internal grayscale and small timing marks down the edge of the document. However, care must be taken with the document design so as not to put the marks too closely together, and OMR works best when the user has an incentive to ensure that the marks are filled in carefully.

Optical Character Recognition (OCR and ICR) engines can achieve high recognition rates equal to human accuracy when documents are properly designed, printed, and controlled.

MICR (Magnetic Ink Character Recognition) was developed to permit the effective processing of checks. Checks consist of a single line of numeric data, and the font used (E-13B or CMC7) is highly stylized and printed with special magnetically conducting ink. Check and remittance readers were equipped with a magnetic reader that analyzed the graph created from a stylized number font and was able to accurately interpret them.

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