UHWR Universal Hand Writing Recognition
Acronym Definition
UHWR UltraHawke Weighbridges Review
UHWR United Healthcare Workers Resource
UHWR: unilateral half-waved rectification
UHWR: Unicursal Hexagram With Rose
UHWR Universal Half-Wave Rectifier
UHWR Universal Half-Wave Retarder
UHWR Universal Hand Writing Recognition
UHWR United Hazardous Waste Reduction
UHWR Universal Heavy Water Reactor
UHWR Universal Hot Water Return
UHWR Universal Hot Wet Rock
UHWR Universal Hull Weight Ratio
UHWR Universal Hand Writing Recognition
Handwriting recognition is the ability of a computer to receive intelligible
handwritten input. The image of the written text may be sensed "off line" from a
piece of paper by optical scanning (optical character recognition).
Alternatively, the movements of the pen tip may be sensed "on line", for example
by a pen-based computer screen surface.
Handwriting recognition principally entails optical character recognition.
However, a complete handwriting recognition system also handles formatting,
performs correct segmentation into characters and finds the most plausible
words.
On-line recognition
On-line handwriting recognition involves the automatic conversion of text as it
is written on a special digitizer or PDA, where a sensor picks up the pen-tip
movements X(t),Y(t) as well as pen-up/pen-down switching. That kind of data is
known as digital ink and can be regarded as a dynamic representation of
handwriting. The obtained signal is converted into letter codes which are usable
within computer and text-processing applications.
The elements of an on-line handwriting recognition interface typically include:
a pen or stylus for the user to write with.
a touch sensitive surface, which may be integrated with, or adjacent to, an
output display.
a software application which interprets the movements of the stylus across the
writing surface, translating the resulting curves into digital text.
Handwriting recognition is commonly used as an input method for PDAs. The first
PDA to provide written input was the Apple Newton, which exposed the public to
the advantage of a streamlined user interface. However, the device was not a
commercial success, owing to the unreliability of the software, which tried to
learn a user's writing patterns. By the time of the release of the Newton OS
2.0, wherein the handwriting recognition was greatly improved, including unique
features still not found in current recognition systems such as modeless error
correction, the largely negative first impression had been made. Another effort
was Go's tablet computer using Go's Penpoint operating system and manufactured
by various hardware makers such as NCR and IBM. IBM's ThinkPad tablet computer
was based on Penpoint operating system and used IBM's handwriting recognition.
This recognition system was later ported to Microsoft Windows for Pen Computing,
and IBM's Pen for OS/2. None of these were commercially successful.
Palm later launched a successful series of PDAs based on the Graffiti®
recognition system. Graffiti improved usability by defining a set of pen strokes
for each character. This narrowed the possibility for erroneous input, although
memorization of the stroke patterns did increase the learning curve for the
user.
A modern handwriting recognition system can be seen in Microsoft's operating
system running on Tablet PCs (notably Windows XP Tablet PC Edition and Windows
Vista). It is based on CalliGrapher, a newer version of the same handwriting
recognition software that was used on Newton OS 2.0, which in 1999 Microsoft
licensed from ParaGraph International (now PhatWare Corp).
A Tablet PC is a special notebook computer that is outfitted with a digitizer
tablet and a stylus, and allows a user to handwrite text on the unit's screen.
The operating system recognizes the handwriting and converts it into typewritten
text. Windows Vista includes personalization features that learn a user's
writing patterns and/or vocabulary for English, Japanese, Chinese Traditional,
Chinese Simplified and Korean. The features include a 'personalization wizard'
that prompts for samples of a user's handwriting and uses them to retrain the
system for higher accuracy recognition. This system is distinct from the less
advanced handwriting recognition system employed in its Windows Mobile OS for
PDAs.
In recent years, several attempts were made to produce ink pens that include
digital elements, such that a person could write on paper, and have the
resulting text stored digitally. The success of these products is yet to be
determined.
Although handwriting recognition is an input form that the public has become
accustomed to, it has not achieved widespread use in either desktop computers or
laptops. It is still generally accepted that keyboard input is both faster and
more reliable. As of 2006, many PDAs offer handwriting input, sometimes even
accepting natural cursive handwriting, but accuracy is still a problem, and some
people still find even a simple on-screen keyboard more efficient.
Off-line recognition
Off-line handwriting recognition involves the automatic conversion of text in an
image I(x,y) into letter codes which are usable within computer and
text-processing applications. The data obtained by this form is regarded as a
static representation of handwriting.
The technology is successfully used by businesses which process lots of
handwritten documents, like insurance companies. The quality of recognition can
be substantially increased by structuring the document (by using forms).
The off-line handwriting recognition is comparatively difficult. As different
people have different handwriting styles, so it becomes difficult to recognize
the handwriting by computer. Nevertheless, limiting the range of input can allow
recognition to improve. For example, the ZIP code digits are generally read by
computer to sort the incoming mail.
Research
Handwriting Recognition has an active community of academics studying it. The
biggest conferences for handwriting recognition are the International Workshop
for Handwriting Recognition (IWFHR), held in even-numbered years, and the
International Conference for Document Analysis and Retrieval (ICDAR), held in
odd-numbered years. Both of these conferences are organized under the auspices
of the IEEE. Active areas of research include:
Online Recognition
Offline Recognition
Signature Verification
Postal-Address Interpretation
Bank-Check Processing

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