Optical Character Recognition

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Summary
Character recognition techniques associate a symbolic identity with the image of character.
Character recognition is commonly referred to as optical character recognition (OCR),
as it deals with the recognition of optically processed characters. The modern version of
OCR appeared in the middle of the 1940’s with the development of the digital computers.
OCR machines have been commercially available since the middle of the 1950’s. Today
OCR-systems are available both as hardware devices and software packages, and a few
thousand systems are sold every week.


The Future of OCR
Through the years, the methods of character recognition has improved from quite primitive
schemes, suitable only for reading stylized printed numerals, to more complex and
sophisticated techniques for the recognition of a great variety of typeset fonts and also
handprinted characters. Below the future of OCR when it comes to both research and areas
of applications, is briefly discussed.
6.1


Future improvements
New methods for character recognition are still expected to appear, as the computer technology
develops and decreasing computational restrictions open up for new approaches.
There might for instance be a potential in performing character recognition directly on
grey level images. However, the greatest potential seems to lie within the exploitation of
existing methods, by mixing methodologies and making more use of context


Future needs
Today optical character recognition is most successful for constrained material, that is
documents produced under some control. However, in the future it seems that the need for
constrained OCR will be decreasing. The reason for this is that control of the production
process usually means that the document is produced from material already stored on a
computer.

Optical Character Recognition(OCR )

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What is OCR?
OCR is the acronym for Optical Character Recognition. This technology allows a machine to
automatically recognize characters through an optical mechanism. Human beings recognize many objects
in this manner our eyes are the "optical mechanism." But while the brain "sees" the input, the ability to
comprehend these signals varies in each person according to many factors. By reviewing these variables,
we can understand the challenges faced by the technologist developing an OCR system.
First, if we read a page in a language other than our own, we may recognize the various characters, but be
unable to recognize words. However, on the same page, we are usually able to interpret numerical
statements - the symbols for numbers are universally used. This explains why many OCR systems
recognize numbers only, while relatively few understand the full alphanumeric character range.


History of OCR
The engineering attempts at automated recognition of printed characters started prior to World War II.
But it was not until the early 1950's that a commercial venture was identified that justified necessary
funding for research and development of the technology. This impetus was provided by the American
Bankers Association and the Financial Services Industry. They challenged all the major equipment
manufacturers to come up with a "Common Language" to automatically process checks. After the war,
check processing had become the single largest paper processing application in the world. Although the
banking industry eventually chose Magnetic Ink Recognition (MICR), some vendors had proposed the
use of an optical recognition technology. However, OCR was still in its infancy at the time and did not
perform as acceptably as MICR. The advantage of MICR was that it is relatively impervious to change,
fraudulent alteration and interference from non-MlCR inks.


Where are we today?
The advent of the array method of scanning, coupled with the higher speeds and more compact
computing power, has led to the concept of "Image Processing". Image processing does not have to
utilize optical recognition to be successful. For example, the ability to change any document to an
electronically digitized item may effectively replace microfilm devices. This provides the user a much
more convenient method of sorting images compared to handling actual documents or microfilm pictures.
Image processing relies on larger more complex arrays than early third generation OCR scanners.



What are its Applications?
OCR has been used to enter data automatically into a computer for dissemination and processing. The
earliest of systems was dedicated to high volume variable data entry. The first major use of OCR was in
processing petroleum credit card sales drafts. This application provides recognition of the purchaser from
the imprinted credit card account number and the introduction of a transaction. The early devices were
coupled with punch units which made small holes to be read by the computer. As computers and OCR
devices became more sophisticated, the scanners provided direct access into the CPU (computer
processing unit). This quickly lead to the payment processing of credit card purchases, known as "remittance
processing". These two applications are still the two major applications for OCR.