Integrated morphological image information method for complex transformed images

This paper presents new recognition method for handwritten Chinese characters. A number of integrated morphological image information based on complex transformed images and subareas is used to get a good recognition rate. Similarity by morphological features are used for recognition. Complex images are obtained by the distance transform and nonlinear normalization. Instead of selective use of complex image information and integrated image information, the general similarity of each similarity based on complex images, subareas and integrated image information is used to get good recognition. General similarity is based on the deviation value of each similarity. We obtained a recognition rate of 99.71% for ETL-9, the best in the world