Abstract:
Pattern matching method is one of the major principles used for character
recognition. This method is applied to the hand written numerical characters. In this
thesis we investigated dynamic search process to recognize a digit. This method conducts
an adaptive matching between reference pattern and a handwritten input digit. This input
digit is actually converted to bit map format which is subsequently compared to the
reference digit. This thesis uses the reward-punishment approach for all the algorithms
developed for recognition. For this purpose it uses a special type of weighting factor for
reward and punishment. This is used as conditional weighting factor. According to this
weighting factor, the segments of the reference digits are classified into three types of
segments to give a digit either reward or punishment. According to this weighting factor
every reference digit gains or losses scores in proportional to the length of the segment
and weighting factor. The reference digit giving maximum score can be declared as the
candidate for a valid digit if it can overcome its threshold score.
The first approach was to search only in the specific direction and area in input
digit. It permits no flexibility, no rotation and no shearing of the input numeric character.
The recognition of hand written characters is a special kind of complex
mathematical problem, because the different distortions present in hand written character
set make it difficult to produce a distinct set identification. For this reason at the later
stages, the reference pattern vectors were permitted to accept aberrations to some extent
in the direction of the input digit to cope with abrupt aberrations in the input pattern line
segments. This improved the flexibility of matching. For this purpose, rotation and
shearing to some extent is performed in the input pattern. This approach helps to
recognize the hand written numeric characters. which are italic.
