21-05-2012, 05:09 PM
Visual Character Recognition using Artificial Neural Networks
[attachment=22627]
INTRODUCTION:
The recognition of characters from
scanned images of documents has been a
problem that has received much
attention in the fields of image
processing, pattern recognition and
artificial intelligence. Classical methods
in pattern recognition do not as such
suffice for the recognition of visual
characters due to the following reasons:
IMAGE DIGITIZATION:
When a document is put to visual
recognition, it is expected to be
consisting of printed (or handwritten)
characters pertaining to one or more
scripts or fonts. This document however,
may contain information besides optical
characters alone. For example, it may
contain pictures and colors that do not
provide any useful information in the
instant sense of character recognition. In
addition, characters which need to be
singly analyzed may exist as word
clusters or may be located at various
points in the document. Such an image is
usually processed for noise-reduction
and separation of individual characters
from the document.
LEARNING MECHANISM:
In the employed system, a highly
simplified architecture of artificial neural
networks is used. For purpose of easy
understanding, the learning mechanism
of the neural network is described first
and its architecture is described next, in
section [4.].
[attachment=22627]
INTRODUCTION:
The recognition of characters from
scanned images of documents has been a
problem that has received much
attention in the fields of image
processing, pattern recognition and
artificial intelligence. Classical methods
in pattern recognition do not as such
suffice for the recognition of visual
characters due to the following reasons:
IMAGE DIGITIZATION:
When a document is put to visual
recognition, it is expected to be
consisting of printed (or handwritten)
characters pertaining to one or more
scripts or fonts. This document however,
may contain information besides optical
characters alone. For example, it may
contain pictures and colors that do not
provide any useful information in the
instant sense of character recognition. In
addition, characters which need to be
singly analyzed may exist as word
clusters or may be located at various
points in the document. Such an image is
usually processed for noise-reduction
and separation of individual characters
from the document.
LEARNING MECHANISM:
In the employed system, a highly
simplified architecture of artificial neural
networks is used. For purpose of easy
understanding, the learning mechanism
of the neural network is described first
and its architecture is described next, in
section [4.].