handwritten character recognition using block wise segmentation technique (bst) in neural network...
TRANSCRIPT
Handwritten Character Recognition Using Block wise Segmentation
Technique (BST) in Neural Network
47th Annual Convention of the Computer Society of India
International Conference on Intelligent Infrastructure
Science City Kolkata December 1-2, 2012
Presented By: Apash Roy, CSA, University of North Bengal
Introduction
Presented By: Apash Roy, CSA, University of North Bengal
• Broad area of application• Still Now the task is in an ease of Interest
Important properties of an Artificial Neural
Network
• Network topology
• Encoding scheme
• Learning algorithm(Supervised and Unsupervised learning)
Presented By: Apash Roy, CSA, University of North Bengal
Pre-Processing
Apash Roy, CSA, University of
North Bengal
Hard Copy Image
Scanner / camera / ...
Pre-processing
Vector with Binary value
Pre-Processing . . .
Apash Roy, CSA, University of
North Bengal
0 0 0 0 1 1 1 0 0 0 0 0 0 0 1 1 1 0 0 0 0 0 0 1 1 0 1 1 0 0 0 0 1 1 0 0 0 1 1 0 0 1 1 0 0 0 0 1 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 1 1 1 1 0 0 0 0 0 0 1 1 1 1 0 0 0 0 0 0 1 1 1 1 0 0 0 0 0 0 1 1
0 0 0 0 0 0 0 0 0 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 0 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 0 0 0 1 1 1 0 0 0 0 0 0 0 0 0 0 1 1 1 0 0 0 0 0 1 1 1 0 0 0 0 0 0 0 0 1 1 1 0 0 0 0 0 0 0 1 1 1 0 0 0 0 0 0 1 1 1 0 0 0 0 0 0 0 0 0 1 1 1 0 0 0 0 1 1 1 0 0 0 0 0 0 0 0 0 0 0 1 1 1 0 0 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 0 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 11 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1
0 0 1 0 00 1 0 1 0 1 1 1 1 11 0 0 0 11 0 0 0 1
Binary representation of ‘A’ in three different size.
Perceptron learning
wij(new) = wij(old) + c(di - yi)xi
where,
wij : the connection weight from ith input element xi of X to the jth neuron of the network.
di and yi :the desired and actual output of jth
neuron.
c :the small positive constant representing the learning rate.
Apash Roy, CSA, University of North Bengal
Some Results
Presented By: Apash Roy, CSA, University of North Bengal
Characters No. of Variants No of success Percentage
A 5 5 100%
B 5 4 80%
C 5 5 100%
D 5 4 80%
E 5 5 100%
Thank You
Apash RoyDepartment of Computer Science and
ApplicationThe university of North Bengal
Presented By: Apash Roy, CSA, University of North Bengal