Cataloged from PDF version of article.Online automatic recognition of handwritten text has been an ongoing research
problem for four decades. It is used in automated postal address and ZIP code and
form reading, data acquisition in bank checks, processing of archived institutional
records, automatic validation of passports, etc. It has been gaining more interest
lately due to the increasing popularity of handheld computers, digital notebooks
and advanced cellular phones. Traditionally, human-machine communication has
been based on keyboard and pointing devices. Online handwriting recognition
promises to provide a dynamic means of communication with computers through
a pen like stylus, not just an ordinary keyboard. This seems to be a more natural
way of entering data into computers.
In this thesis, we develop a character recognition system that combines the
advantage of both on-line and off-line systems. Using an USB CCD Camera,
positions of the pen-tip between frames are detected as they are written on a sheet
of regular paper. Then, these positions are used for calculation of directional
information. Finally, handwritten character is characterized by a sequence of
writing directions between consecutive frames. The directional information of
the pen movement points is used for character pre-classification and positional
information is used for fine classification. After characters are recognized they are
passed to LaTeX code generation subroutine. Supported LaTeX environments are
array construction, citation, section, itemization, equation, verbatim and normal
text environments. During experiments a recognition rate of 90% was achieved.
The main recognition errors were due to the abnormal writing and ambiguity
among similar shaped characters.Öksüz, ÖzcanM.S
