OMR (Optical Mark Recognition) and OCR (Optical Character Recognition) are two methods of getting information from paper into a digital format. Although both seem to work in similar ways, there is a major difference between OMR and OCR. The responsibility of OMR is only to tell whether a mark is present or not in a predetermined area. OCR also detects the presence of marks but its task doesn’t stop there. OCR also needs to determine what that mark is. It is usually limited to a single language to limit the possible characters and enhance the accuracy.
The primary purpose of OCR is to eliminate the need to re-encode a document that has already been printed. OCR takes an image of a printed document, attempts to recognize all the characters on a page, then string the characters together into an editable document that can then be edited in a word processor and mostly resembles the original document. Although not 100% accurate, it significantly reduces the effort needed to recreate the document. In comparison, the main use of OMR is in tabulating or evaluating data from a large number of documents. The biggest example of this is in grading simple multiple choice exams. OMR is also used to tabulate data from census or surveys using the same method. OMR is much faster compared to doing it by hand since the machine can process a sheet in an instant.