Online a computer to detect and understand intelligible

Online handwriting analysis is a
challenging research area for the last few decades. To recognize with perfect
prediction some pre-processing steps are essential. In this paper one of the
important pre-processing steps dehooking is presented. Here we consider Bengali
online handwritten Characters and words as sample for removing hooks. Hooks are
basically common artifacts during fast writing by people. Hooks are very common
issue present at the beginning in very rare case and the end of
character stroke in maximum case and are generated by the pen-down and pen up
movements respectively. Dehooking is the process of eliminating such unwanted strokes that appear
due to inaccuracies in pen down position. Dehooking algorithms are applied to
remove hooks. Here, strokes are detected by comparing the number of points with
a threshold value. If the value is greater than the threshold value, the mark
is retained or it is removed otherwise. In this new and innovative approach we focus on the
dehooking at the end of character stroke and consider last 20 percent of each
stroke for checking, according to distance from the co-ordinate of the first
pixel. In last 20 percent of a stroke, we calculated angle among three
consecutive pixels. If in a particular point, angle among three consecutive pixels
is falling suddenly then immediately we pointed out that point. After pointing
out the angle falling place we checked the entire remaining pixel after that
point, whether all the remaining points are getting fade slowly or not. If it
is found that all the remaining points aregetting fade slowly then it can be
assumed that it a hook. After detecting the hook for a particular stroke we removed
all the remaining pixels from the falling angle place so that hook can be
removed and the handwritten character will be hook less.I tested 1200 English
and 1600 Bengali online handwritten characters and we got 97.02 percent of
accuracy.Online Handwriting recognition is a procedure
of a computer to detect and understand intelligible handwritten characters,
words, sentence or paragraph input from a touch sensitive or pen sensitive
input sources such as Pen tablets, PDA, touch-screens and other devices. The
movements of the pen tip may be sensed “on line”, but it is
comparatively difficult task to recognize with great accuracy because in case
of online handwriting only co-ordinate values are known to us. Handwriting
recognition principally entails optical character recognition. However, a
complete handwriting recognition system also handles pre-processing steps,
formatting, performs correct segmentation into characters, normalization and
finds the most plausible Characters and words. 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 as well as
pen-up/pen-down switching and covert into vectors or matrix form. This kind of
data is known as digital ink and can be regarded as a digital representation of
handwriting. The obtained signal is converted into letter codes which are
usable within computer and text-processing applications.