Different approach to designing neural networks for similar handwritten Chinese character recognition

Abstract

The input images of Chinese characters are normally preprocessed using different image processing techniques before the main classification in the handwritten Chinese character recognition. The authors proposed a different approach to the system philosophy of solving the handwritten Chinese character recognition problem where no preprocessing is necessary. The Chinese characters are treated as ideographs. The proposed system consists of a Rough Classifier which trigger the different Fine Classifiers. Each classifier is an optimized artificial neural network using genetic algorithms. A reduced system has been implemented. The result shows that the proposed system has higher recognition rate than the similar systems reported and is more efficiency.