电子科技学刊
電子科技學刊
전자과기학간
JOURNAL OF ELECTRONIC SCIENCE AND TECHNOLOGY OF CHINA
2014年
1期
85-89
,共5页
Angle features%artificial neural network%signature recognition
Handwritten signature recognition is presented based on an angle feature vector by using the artificial neural network (ANN) in this research. Each signature image will be represented by an angle vector. The feature vector will constitute the input to the ANN. The collection of signature images is divided into two sets. One set will be used for training the ANN in a supervised fashion. The other set which is never seen by the ANN will be used for testing. After training, the ANN will be tested by recognizing the signatures. When a signature is classified correctly, it is considered correct recognition, otherwise it is a failure. The achieved recognition rate of this system is 94%.
