Abstract:
In this paper an attempt is made to develop
Myanmar handwritten character recognition
system. Character recognition is an important
area in image processing and pattern
recognition fields. The aim of character
recognition is to translate human readable
characters to machine readable characters. The
paper describes the process of character
recognition using morphological operators with
the competitive neural trees. The morphological
operators are used to extract the edge of each
character image. Then, competitive neural trees
(CNeT) are used for classification. It is one of
the fast supervised neural networks with high
performance. The main advantage of the CNeT is
its structured, self-organizing architecture that
allows for short learning and recall times. High
speed recognition rates can be gained by using
CNeT.
