Detection of Connecting Points in Thai Printed Characters by Combining Inductive Logic Programming with Backpropagation Neural Network

Mantova, Italy September 17-September 19

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http://doi.ieeecomputersociety.org/10.1109/ICIAP.2003.1234049

12th International Conference on Imag ...

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	Sukree Sinthupinyo, Luepol Pipanmaekaporn, Boonserm Kijsirikul, "Detection of Connecting Points in Thai Printed Characters by Combining Inductive Logic Programming with Backpropagation Neural Network," Image Analysis and Processing, International Conference on, pp. 196, 12th International Conference on Image Analysis and Processing (ICIAP'03), 2003.

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	@article{ 10.1109/ICIAP.2003.1234049, author = {Sukree Sinthupinyo and Luepol Pipanmaekaporn and Boonserm Kijsirikul}, title = {Detection of Connecting Points in Thai Printed Characters by Combining Inductive Logic Programming with Backpropagation Neural Network}, journal ={Image Analysis and Processing, International Conference on}, volume = {0}, year = {2003}, isbn = {0-7695-1948-2}, pages = {196}, doi = {http://doi.ieeecomputersociety.org/10.1109/ICIAP.2003.1234049}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }

	RefWorks Procite/RefMan/Endnote	x
	TY - CONF JO - Image Analysis and Processing, International Conference on TI - Detection of Connecting Points in Thai Printed Characters by Combining Inductive Logic Programming with Backpropagation Neural Network SN - 0-7695-1948-2 SP EP A1 - Sukree Sinthupinyo, A1 - Luepol Pipanmaekaporn, A1 - Boonserm Kijsirikul, PY - 2003 KW - Connected Characters KW - Inductive Logic Programming and Backpropagation Neural Networks VL - 0 JA - Image Analysis and Processing, International Conference on ER -

Sukree Sinthupinyo, Thammasat University

Luepol Pipanmaekaporn, Thammasat University

Boonserm Kijsirikul, Chulalongkorn University

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.

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, pp.196, 12th International Conference on Image Analysis and Processing (ICIAP'03), 2003

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