NDLI: Thai printed character recognition by combining inductive logic programming with backpropagation neural network

Content Provider	IEEE Xplore Digital Library
Author	Kijsirikul, B. Sinthupinyo, S. Supanwansa, A.
Copyright Year	1998
Description	Author affiliation: Dept. of Comput. Eng., Chulalongkorn Univ., Bangkok, Thailand (Kijsirikul, B.)
Abstract	Several approaches to Thai printed character recognition have been proposed such as comparing heading of character, backpropagation neural network (BNN), fuzzy logic and syntactic method, etc. This paper presents a new approach that combines two learning algorithms, i.e. inductive logic programming (ILP) and backpropagation neural network. After features of character images are extracted, they are employed to construct examples for training an ILP algorithm to learn rules that define the characters. The learned rules are then used to classify the unseen data. However, since some character image, especially the noisy image, may not exactly match with any rule, we then employ BNN for approximately matching the image with the rules. Experimental results demonstrate that the accuracy of rules learned by ILP without the help of BNN is comparable to other methods. Moreover, combining BNN with ILP achieves higher accuracy than the other methods tested in our experiment.
Starting Page	539
Ending Page	542
File Size	391317
Page Count	4
File Format	PDF
ISBN	0780351460
DOI	10.1109/APCCAS.1998.743876
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1998-11-24
Publisher Place	Thailand
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Character recognition Logic programming Feature extraction Neural networks Fuzzy logic Backpropagation algorithms Data mining Testing Noise reduction Computer networks
Content Type	Text
Resource Type	Article

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