Despite the fact that Chinese characters are composed of radicals and that Chinese people usually formulate their knowledge of Chinese characters as a combination of radicals, very few studies have focused on a character decomposition approach to recognition, i.e., recognizing a character by first extracting and recognizing its radicals. Such an approach is adopted and the problem of how to extract radical sub-images from character images is particularly addressed. A radical extraction algorithm based on deformable templates (DTs) has been developed. The advantage of the character decomposition approach is demonstrated by feeding the extracted radical images to an adopted structural based Chinese character recognizer whose outputs are then combined to produce the class label of the input character. Simulation results show that the performance of the adopted Chinese character recognition system can be improved significantly when the character decomposition approach is used.

In this article a variation of fuzzy Petri net (FPN) model is proposed to accommodate for the possibility of mapping fuzzy production rule (FPR) having different threshold values in their propositions into FPN. the purpose of assigning a different threshold value for each proposition in the FPR and of using the rule checking and evaluation method proposed here is to prevent misfiring of the rule, which can result with other methods; the purpose of having variation of FPN model is to capture and represent more information of FPR in the FPN model. the rule checking and evaluation method is an enhancement of the approach proposed by Yeung (D. S. Yeung et al., Proceedings of the 6th International Conference on System Research Informatics and Cybernetics, Germany, 1992). As mentioned by the authors, the degree of subsethood between two vectors is the basis of the method. the subsethood method will first be used to make certain that each input value for the proposition in the antecedent is greater than or equal to its corresponding threshold value. When such condition holds, the subsethood method is used to infer the degree of truth of the consequent of the rule. an enhanced fuzzy reasoning algorithm is included. Comparison of this method with other methods is presented. Future research work in determining acceptable threshold values and certainty factors is addressed. © 1994 John Wiley & Sons, Inc.