| Abstract |
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This paper presents a method for detecting the connecting points in connected Thai printed characters. In Thai Optical Character Recognition systems, an important problem that decreases the accuracy is the connected characters. These characters could cause the errors in segmentation process. To attack this problem, we first extract the features of the connecting points in the character images. Then, we employ Inductive Logic Programming to produce the rules that will be used to classify the unseen images. Finally, we use a Backpropagation Neural Network to make these rules more flexible. The experimental results show that our method achieves 94.94% accuracy.
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 Additional Information
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Index Terms- Connected Characters, Inductive Logic Programming and Backpropagation Neural Networks
Citation:
Sukree Sinthupinyo, Luepol Pipanmaekaporn, Boonserm Kijsirikul,
"Detection of Connecting Points in Thai Printed Characters by Combining Inductive Logic Programming with Backpropagation Neural Network,"
iciap,
p. 196,
12th International Conference on Image Analysis and Processing (ICIAP'03),
2003
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