Abstract:
This paper presents the development of English
Handwritten character recognition system, which
uses local and global features of English characters
by applying the concept of feature feeding. After each
character is extracted, the features are fed to the
recognition engine. A well-known Multi-layer
Feedforward neural network with backpropagation
learning algorithm is chosen for its fast processing
time and its good performance for pattern
recognition problems. Backpropagation Learning
algorithm is prefered for training of neural network.
Training set occurs of various English characters
collected from different people. The characters are
presented directly to the network and correctly sized
in pre-processing. In applying with free-hand
English single characters, the average recognition
rate of 91% has been achieved this confirms that the
proposed approach is suitable for the development of
English handwritten character recognition system.
Recognition percentage of the system is higher than
acceptable level. Input data, network parameters and
training period affect the result.
