Optical Mark Recognition (also called
Optical Mark Reading and
OMR) is
the process of capturing human-marked data from
document forms such as surveys and
tests.
OMR Background

OMR test form, with registration marks
and drop-out colors, designed to be scanned by dedicated OMR
device
Many traditional OMR devices work with a dedicated
scanner device that shines a beam of light onto the
form paper. The contrasting
reflectivity at predetermined positions on a
page is then utilized to detect the marked areas because they
reflect less light than the blank areas of the paper.
Some OMR devices use forms which are preprinted onto 'transoptic'
paper and measure the amount of light which passes through the
paper, thus a mark on either side of the paper will reduce the
amount of light passing through the paper.
In contrast to the dedicated OMR device, desktop OMR software
allows a user to create their own forms in a word processor and
print them on a laser printer. The OMR software then works with a
common desktop image scanner with a document feeder to process the
forms once filled out.
OMR is generally distinguished from
optical character recognition
by the fact that a complicated
pattern recognition engine is not
required. That is, the marks are constructed in such a way that
there is little chance of not reading the marks correctly. This
does require the image to have high contrast and an
easily-recognizable or irrelevant shape. A related field to OMR and
OCR is the recognition of
barcodes such as
the
UPC bar code found on product
packaging.
One of the most familiar applications of optical mark recognition
is the use of #2 (HB in Europe) pencil bubble
optical answer sheets in
multiple choice question examinations. Students mark their answers, or
other personal information, by darkening circles marked on a
pre-printed sheet. Afterwards the sheet is automatically graded by
a scanning machine. In most European countries, a horizontal or
vertical 'tick' in a rectangular 'lozenge' is the most commonly
used type of OMR form, the most familiar application being the UK
National lottery form. Lozenge marks are a later technology and
have the advantage of being easier to mark and easier to erase. The
large 'bubble' marks are legacy technology from the very early OMR
machines that were so insensitive a large mark was required for
reliability. In most Asian countries, a special marker is used to
fill in an
optical answer
sheet. Students, likewise mark answers or other information via
darkening circles marked on a pre-printed sheet. Then the sheet is
automatically graded by a scanning machine.
Many of today's OMR applications involve people filling in
specialized forms. These forms are optimized for computer scanning,
with careful registration in the printing, and careful design so
that ambiguity is reduced to the minimum possible. Due to its
extremely low error rate, low cost and ease-of-use, OMR is a
popular method of tallying votes.
OMR Software

Plain paper OMR survey form, without
registration marks and drop-out colors, designed to be scanned by
an image scanner and OMR software
OMR Software is a computer software application that makes OMR
possible on a desktop computer by using an
Image scanner to process surveys, tests,
attendance sheets, checklists, and other plain-paper forms printed
on a laser printer.
The need for OMR software originated because early Optical Mark
Recognition systems were designed to use dedicated scanners and
special pre-printed forms with drop-out colors and registration
marks. Such forms typically cost USD $0.10 to $0.19 a page. In
contrast, OMR Software users design their own mark-sense forms with
a word processor or built-in form editor and print them locally on
a laser printer saving themselves thousands of dollars on large
numbers of forms.
History
Optical mark recognition (OMR) is the scanning of paper to detect
the presence or absence of a mark in a predetermined position.
Optical mark recognition has evolved from several other
technologies. In the early 1800’s and 1900’s patents were given for
machines that would aid the blind.
OMR is now used as an input device for data entry. Two early forms
of OMR are paper tape and punch cards which use actual holes
punched into the medium instead of pencil filled circles on the
medium. Paper tape was used as early as 1857 as an input device for
telegraph. Punch cards were created in 1890 and were used as input
devices for computers. The use of punch cards declined greatly in
the early 1970’s with the introduction of personal computers. With
modern OMR, where the presence of a pencil filled in bubble is
recognized, the recognition is done via an optical scanner.
The first
mark sense scanner was the
IBM 805 Test Scoring
Machine; this read marks by sensing the electrical conductivity
of graphite pencil lead using pairs of wire brushes that scanned
the page. In the 1930s, Richard Warren at
IBM
experimented with optical mark sense systems for test scoring, as
documented in US Patents 2,150,256 (filed in 1932, granted in 1939)
and 2,010,653 (filed in 1933, granted in 1935). The first
successful optical mark-sense scanner was developed by
Everett Franklin Lindquist as
documented in US Patent 3,050,248 (filed in 1955, granted in 1962).
Lindquist had developed numerous standardized educational tests,
and needed a better test scoring machine than the then-standard IBM
805.
The
rights to Lindquist's patents were held by the Measurement Research
Center until 1968, when the University of Iowa
sold the operation to Westinghouse Corporation.
Westinghouse Learning Corporation was acquired by National Computer
Systems in 1983; in 2000,
Pearson
Education acquired NCS. IN 2008, NCS Pearson was acquired by
Scantron.
During the same period,
IBM also developed a
successful optical mark-sense test-scoring machine, as documented
in US Patent 2,944,734 (filed in 1957, granted in 1960). IBM
commercialized this as the IBM 1230 Optical mark scoring reader in
1962. This and a variety of related machines allowed IBM to migrate
a wide variety of applications developed for its
mark sense machines to the new optical
technology. These applications included a variety of inventory
management and trouble reporting forms, most of which had the
dimensions of a standard
punched
card.
While the other players in the educational testing arena focused on
selling scanning services,
Scantron
Corporation, founded in 1972, had a different model, distribute
inexpensive scanners to schools and make profits from selling the
test forms. As a result, many people came to think of all
mark-sense forms (whether optically sensed or not) as
scantron forms. Scantron operates as a subsidiary of
M&F Worldwide(MFW) and provides testing and assessment systems
and services and data collection and analysis services to
educational institutions, businesses and government.
Like Scantron,
Chatsworth Data Corporation is a seller of OMR
scanners. Founded in 1971, Chatsworth has always focused on selling
the scanners themselves, mostly as OEM products incorporated into
systems developed by others.
OMR has been used in many situations as mentioned below. The use of
OMR in inventory systems was a transition between punch cards and
bar codes and is not used as much for this purpose. OMR is still
used extensively for surveys and testing though.
General
The use of OMR is not only limited to schools or data collection
agencies; many businesses and health care agencies use OMR to
streamline their data input processes and reduce input error (“Who
uses Remark Office OMR”, n.d). OMR, OCR, and ICR technologies all
provide a means of data collection from paper forms. OMR may also
be done using an OMR (discrete read head) scanner or an imaging
scanner.
Applications
There are many other applications for OMR, for example:
- In the process of institutional research
- Community surveys
- Consumer surveys
- Tests/assessments
- Evaluations/Feedback
- Data compilation
- Product evaluation
- Time sheets/Inventory counts
- Membership subscription forms
- Lotteries/Voting (“Who uses Remark Office OMR or TestAnyTime”,
n.d.)
- Geocoding (e.g. postal codes)
Fields
OMR has different fields to provide the format the questioner
desires. These fields include:
- Multiple, where there are several options but only one is
chosen, ABCDE, 12345, completely disagree, disagree, indifferent,
agree, completely agree, etc.
- Grid, the bubbles or lines are set up in a grid format for the
user to fill in a phone number, name, ID number and so on.
- Add, total the answers to a single value
- Boolean, answering yes or no to all that apply
- Binary, answering yes or no to only one (Martin, n.d.).
Capabilities/requirements
In the past and presently, some OMR systems require special paper,
special ink and a special input reader (Bergeron, 1998). This
restricts the types of questions that can be asked and does not
allow for much variability when the form is being input. Progress
in OMR now allows users to create and print their own forms and use
a scanner (preferably with a document feeder) to read the
information (Bergeron, 1998). The user is able to arrange questions
in a format that suits their needs while still being able to easily
input the data (LoPresti, 1996). OMR systems approach one hundred
percent accuracy and only take .005 seconds on average to recognize
marks (Bergeron, 1998). Users can use squares, circles, ellipses
and hexagons for the mark zone. The software can then be set to
recognize filled in bubbles, x’s or check marks (“Intelligence in
Document Imaging”, n.d.).
OMR can also be used for personal use. There are all-in-one
printers in the market that will print the photos the user selects
by filling in the bubbles for size and paper selection on an index
sheet that has been printed. Once the sheet has been filled in, the
individual places the sheet on the scanner to be scanned and the
printer will print the photos according to the marks that were
indicated (M. Meek, personal communication, February 11,
2006).
Disadvantages
There are also some disadvantages and limitations to OMR. If the
user wants to gather large amounts of text, then OMR complicates
the data collection (Green, 2000). There is also the possibility of
missing data in the scanning process, and incorrectly or unnumbered
pages can lead to their being scanned in the wrong order. Also,
unless safeguards are in place, a page could be rescanned providing
duplicate data and skewing the data (Bergeron, 1998).
For the most part OMR provides a fast, accurate way to collect and
input data; however, it is not suited for everyone’s needs.
As a result of the widespread adoption and ease of use of OMR,
standardized examinations consist primarily of multiple-choice
questions, changing the nature of what is being tested.
References
- Bergeron, Bryan P. (1998, August). Optical mark recognition.
Postgraduate Medicine online. Retrieved June 7, 2006 from
http://www.postgradmed.com/issues/1998/08_98/dd_aug.htm
- Bookrags. (n.d.) Optical Character Recognition. Retrieved June
11, 2006, from
http://www.bookrags.com/sciences/computerscience/optical-character-recognition-csci-02.html
- Green, Phil (2000). Optical Scanning Systems. Retrieved June 9,
2006 from http://www.aceproject.org/main/english/et/et72.htm
- Haag, S., Cummings, M., McCubbrey, D., Pinsonnault, A.,
Donovan, R. (2006). Management Information Systems for the
Information Age (3rd ed.).Canada: McGraw-Hill Ryerson.
- LoPresti, Frank and Naphtali, Zvia Segal. (1996) Statisticians’
Lib: Using Scanners and OMR Software for Affordable Data Input.
Statistics and the Social Sciences. Retrieved June 7, 2006 from
http://www.nyu.edu/its/pubs/connect/archives/96fall/loprestistats.html
- Martin, Ann. (n.d.) Data Collection on the Cheap: A System for
Small budgets and Small Organizations. Retrieved June 9, 2006 from
http://www.lco.edu/facstaff/asmnt/Data%20Collection%20on%20the%20Cheap%20Format.ppt#1
- OMR Solutions. (n.d.) Who uses Remark Office OMR Retrieved June
9, 2006 from
http://www.omrsolutions.com/principia/whousesremark.php
- Palmer, Roger C. (1989, Sept) The Basics of Automatic
Identification [Electronic version]. Canadian Datasystems, 21 (9),
30-33
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June 7, 2006 from http://www.tkvision.com/tech/technology.htm
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Scantron Forms Prices
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http://www.gravic.com/remark/officeomr/pdf/Case%20Study%20-%20University%20of%20Arizona.pdf
University of Arizona OMR Case Study
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- Haag, S., Cummings, M., McCubbrey, D., Pinsonnault, A.,
Donovan, R. (2006). Management Information Systems for the
Information Age (3rd ed.).Canada: McGraw-Hill Ryerson.
- Bookrags. (n.d.) Optical Character Recognition. Retrieved June
11, 2006, from
http://www.bookrags.com/sciences/computerscience/optical-character-recognition-csci-02.html
- Yurcik, William J. (n.d.) Optical Character Recognition.
Retrieved June 11, 2006, from
http://www.bookrags.com/sciences/computerscience/input-devices-csci-02.html
- Palmer, Roger C. (1989, Sept) The Basics of Automatic
Identification [Electronic version]. Canadian Datasystems, 21 (9),
30-33
- http://www.scantron.com/press/02_22_2008.aspx
- http://www.bc.edu/research/nbetpp/publications/v2n3.html
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http://findarticles.com/p/articles/mi_hb4723/is_198901/ai_n17287322
- http://www.mandfworldwide.com/
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Forbes.com
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- Palmer, Roger C. (1989, Sept) The Basics of Automatic
Identification [Electronic version]. Canadian Datasystems, 21 (9),
30-33
- Data Management Solutions from Scantron
See also