Abstract:
Character recognition is a very popular research field since 1950’s. A great deal of research
work has been done for various languages specifically in case of English. The recognition
of optical characters is known to be one of the earliest applications of Artificial Neural Networks.
The use of artificial neural network simplifies development of an optical character
recognition application, while achieving highest quality of recognition and good performance.
Although Bangla is one of the most widely spoken languages (over 200 million
people use Bangla as their medium of Communication) of the world, research is acute in
recognition of Bangla characters. Under this context, an effort has been taken globally to
computerize the Bangla language. Compared to English and other language scripts, one of
the major stumbling blocks in Optical Character Recognition (OCR) of Bangla script is the
large number of complex shaped character classes of Bangla alphabet. In addition to 50
basic character classes, there are nearly 160 complex shaped compound character classes in
Bangla alphabet. Dealing with such a large variety of characters with a suitably designed
feature set is a challenging problem. Uncertainty and imprecision is inherent in handwritten
script. Moreover, such a large variety of complex shaped characters, some of which have
close resemblance, makes the problem of OCR of Bangla characters more difficult. Considering
the complexity of the problem, this research makes an attempt to develop a method
for the recognition of Bangla characters using the artificial neural network. Pre-processing
steps involves segmentation and binarization. Features are taken using different feature extraction
procedures. Multilayered neural network is used in the spirit of back-propagation
algorithm for classification as well as recognition of characters. To deal with immense variation
and magnificent diversity of Bangla characters, this effort have widened the area for
many research works to come to light and to bid fair to be accomplished.
Description:
We are thankful to Almighty Allah for his blessings for the successful completion of our
thesis. Our heartiest gratitude, profound indebtedness and deep respect go to our supervisor
Dr. Hasan Sarwar, Professor and Head of the Department, CSE, United International University,
House no. 80, Road 8/A, Sat Masjid Road, Dhanmondi, Dhaka, Bangladesh, for his
constant supervision, affectionate guidance and great encouragement and motivation. His
keen interest on the topic and valuable advices throughout the study was of great help in
completing thesis.
We are especially grateful to the Department of Computer Science and Engineering (CSE)
of Military Institute of Science and Technology (MIST) for providing their all out support
during the thesis work.
Finally, we would like to thank our families and our course mates for their appreciable
assistance, patience and suggestions during the course of our thesis.
