Artificial Neural Network model for handwritten digit recognition based on template matching
Lou Wen-gao · Computer Engineering and Applications Journal · 2008
The shortcomings of the models,established in before,for Handwritten Digit Recognition(HDR) using Artificial Neural Network(ANN) are analyzed.A new method based on template matching is thus put forward.A standard template of handwritten digits 0～9 with 8×12 pels is created in this paper.The standard difference among one digit with the others is existed and picked up.Due to the uncertainty of handwritten digits,the training data,the verification data and testing data are then generated by adding a random number in a certain range to the standard differential value between the handwritten digit and the digits of standard template.The ANN model for HDR based on matching the template with good generalization ability is then established obeying to modeling principles and steps in this paper.The case study shows that the established model has good practicability.The accuracy of testing data is more than 99.6%.