Recognition of Handwritten Text

Recognition of Handwritten Text

Recognition of handwritten text transforms handwritten text into machine-readable text on a computer.

Target users and customers

  • Researchers
  • Developers
  • Integrators

Application sectors

Recognition of printed or handwritten text is heavily used in the mass processing of paper mail, filled-out forms and letters e.g. to insurance companies, and has been covered by the media in connection with the mass digitization of books. New usage patterns will evolve from the better coverage of handwriting and difficult font systems like Arabic or Chinese and from the recognition of text in any form of image data that due to digital cameras and the Internet, is being produced and distributed in ever increasing volumes.


Optical character recognition (OCR) works sufficiently well on printed text but is in particular difficult for handwritten material. This is due to the fact that handwritten material contains a far higher variability than printed one. Methods that have been proven successful in other areas such as speech recognition and machine translation are being exploited to tackle this set of OCR problems.

Technical requirements:

The text needs to be available in digitized form, e.g. through a scanner as part of a digital image or video. Processing takes place on a normal computer.

Conditions for access and use:

RWTH does currently not provide public access to software in this area. Any usage should be subject to a bilateral agreement.



  • RWTH Aachen

Contact details:

Volker Steinbiss

RWTH Aachen University
Lehrstuhl für Informatik 6
Templergraben 55
52072 Aachen