Difference Between OMR and OCR (With Table)

The progress in the field of technology is catching a rapid speed. Every day brings new surprises with it, in the form of new technological inventions (new machines, software, etc.). Earlier all work was done by hand—the process used to take hours to complete.

We should be very grateful to technology for providing us with a hassle-free life. Earlier work used to take hours and a lot of hard work can now be completed in few minutes. OMR and OCR are such software that has proven to be very helpful. They collect data and convert images of human-marked or written, or printed text into machine-encoded form.

OMR vs OCR

The difference between OMR and OCR is that OMR is the abbreviation of optical mark recognition that is used to recognize the check and bubble marks on the paper; mostly exams and surveys, whereas OCR is optical character recognition that is used to recognize the characters from documents and collects and converts it into machine-coded language for editing it.

OMR – known as optical mark recognition, is a technology used to read marked human data. This process captures the data from documents like tests and surveys. It can deduct and read multiple choice papers, questionnaires, etc., with the help of the shaded and lined areas. OMR is also called optical mark reading. The sheets that are scanned by the OMR scanner are then processed by the OMR software. This method made grading in exams easier.

OCR- known as optical character recognition, is a technology that converts the images of any text document electronically into an encoded text in the machine. It is also known as an optical character reader. It is a method that digitizes printed texts and is a form of data entry for data records. This is done so that the data can be electronically edited and stored systematically. It can be used on any scanned documents, photo documents, billboards, text on signs, television broadcasts, etc.

Comparison Table Between OMR and OCR

 Parameters of Comparison OMR OCR
The Full-Form Optical mark recognitionOptical character recognition 
 DefinitionA technology that captures human marked data to determine the presence and location of marked data such as marks with the help of lines and shaded areas. A technology that converts images of texts in any form of data electronically into machine language to determine what it represents and to store it systematically.
 Level of Implementation Easy Comparatively hard to implement
 Application Tests, surveys, voting, geo-coding, product evaluation, etc. Business documents, data entry, bank statements, Google books, etc.
 Also Called Optical mark reader Optical character reader

What is OMR?

OMR is the abbreviation of optical mark recognition (also called optical mark reading); it is computer software. It captures data marked by humans from various documents. The lines or shaded areas on the papers are used to read multiple-choice and questionnaire, examinations, etc.

A heavy OMR scanner machine was invented way back in the 1970s to correct school grading forms that were in the form of bubbles. Since then, heavy OMR machines were used all over the world. The earliest machines were very heavy and not affordable for common people. Later soft logic’s OMR scanner machines were introduced. The artificial intelligence was based on the OMR bubble reading algorithm, and this software removed dependency on heavy OMR machines.

The working process is such that; a dedicated scanning device that projects the paper with a beam of light. The reflectivity on different positions on the paper is used to detect the marked areas. The results are known when the areas reflect comparatively less than the blank areas. Few machines use preprinted form trans optic paper and then measures the amount of light. The specialized forms filled by people in today’s OMR machines are optimized for computer scanning.  

Remark Office OMR (made by Gravic. Inc) used images from common image scanners, which was said to be one of the first software packages. This software was very useful as it saved thousands as it was cheaper than the earlier method. It is a well-known method of tallying votes, used for tests and surveys, feedbacks, lotteries, banking, evaluation, etc. Flatbed scanners and ADF scanners are the two types of document scanners available in the market and are used to scan OMR sheets.

It has an option of different fields to provide us with a preferred format of the questionnaire –

  • Multiple
  • Grid
  • Add
  • Boolean
  • Binary
  • Dotted lines field

OMR machines also come along with a few errors and disadvantages. It can complicate the collection of data of a large amount of text. Data can also go missing in the scanning process; it can scan in the wrong order if pages are not numbered correctly. If the ovals in the paper are outlined too thick, it can even read them as filled.

What is OCR?

OCR is the abbreviation of optical character recognition, also known as optical character reader. It is a technology that converts images of text in any form (written or typed) electronically into a machine-encoded language. It can be used on a photo of a document, texts on signs and billboards, scanned documents, subtitles text, etc. It processes a digital image by locating and recognizing characters.

This method digitizes texts that are printed so that we can easily edit and store data electronically and systematically. It is a type of data entry from any printed paper record. Computer vision, artificial intelligence, etc., are the fields in which OCR can be used in research. OCR as an online service was made available in the 2000s. Traffic sign recognition, data entry for documents such as passports, banks, etc., technology that assists the blind and visually challenged users, etc., are a few uses of OCR.

There is a difference in the working between the earlier versions and the advanced versions. The early system needed a lot of training with each character and used to work slowly because it used to work on one font at a time where the advanced versions can provide a high degree of recognition accuracy and several fonts. The process in an OCR is generally done offline but there also cloud-based services that furnish you with an online OCR API.

There are different techniques used in each stage of the process –

  • Pre-processing – De-skew, despeckle, binarisation, etc.
  • Text recognition – matrix matching, feature extraction, etc.
  • Post-processing – lexicon, near-neighbor analysis, etc.

Main Differences Between OMR and OCR

  1. The full form of OMR is optical mark recognition, whereas the full form of OCR is optical character recognition.
  2. OMR is a technology that captures marked human data to determine the presence and location of marked data such as marks with the help of lines and shaded areas, whereas OCR is a technology that converts images of different forms of texts and data electronically into machine language to determine what it represents and to store it systematically.
  3. OMR is easy to implement, whereas OCR is a little hard to implement.
  4. OMR is also called optical mark reader, whereas OCR is also called optical character reader.
  5. Tests, surveys, voting, geo-coding, product evaluation, etc., are a few uses of OMR, whereas business documents, data entry, bank statements, Google books, etc., are a few uses of OCR.

Conclusion

We must be very grateful to technology; it has made our lives very convenient. We can do difficult tasks in no time and with so much precision. We would have never thought that such things could be possible and that a machine could do our work.

OMR and OCR might seem to work similarly and get anyone confused, but their purposes are different. Technological advancement astonishes in a new way, but nothing can be perfect. Everything comes with different uses, pros, and cons.

References

  1. https://ieeexplore.ieee.org/abstract/document/4725254/
  2. https://www.researchgate.net/profile/Chirag_Patel27/publication/235956427_Optical_Character_Recognition_by_Open_source_OCR_Tool_Tesseract_A_Case_Study/links/00463516fa43a64739000000.pdf
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