OMR | Optical Mark Recognition
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Attributes & Limitations

  • Mark/no mark optical-read, read-only technology
  • Relatively low cost scanning equipment
  • Application-specific forms required, low cost in bulk
  • Accuracy determined by the effectiveness of detecting marks and accommodating the variability in marks.

 

Optical Mark Recognition (OMR) is used for standardized testing as well as course enrollment and attendance in education. Human resource departments across industries use OMR for applications such as benefits enrollment, employee testing, change of employee status, payroll deductions, and user training. Healthcare providers use the technology for registration and surveys, and medical labs for patient evaluations and tracking supply orders and lab services. OMR is also used for time and attendance, labor tracking, inventory management, voting applications, exit surveys, polling, and all manner of questionnaires and evaluation studies. Because it is easy to use and cost effective for opinion tracking, the technology has become a tool for on-location and direct-mail marketing.

 

Generations of students subjected to standardized testing are all too familiar with optical mark recognition, though few are likely to recognize it by name. One of the earliest types of automated data entry, also referred to as mark sense, OMR processes marked data by detecting and measuring reflected light flooding the form. When a mark has been made within a constrained area (with a #2 pencil or more recently, a felt-tipped pen), it absorbs light. Subsequently, electronic circuitry recognizes the mark as valid and sends a digital signal to the computer. The form data, represented by mark positions, are translated to ASCII text records for use in a variety of applications.

 

Another huge application is in lotteries, where participants can quickly and easily mark their selection of numbers on a machine-readable ticket.

 

Although less sophisticated than other optical data collection technologies, OMR can serve certain high-volume data collection applications very cost-effectively because of labor and cost efficiencies. It has a lock on the educational market and is growing steadily in commercial and government applications.


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