Video Based Online Signature Verification

Signature is one of the personal identification methods. In this paper we have proposed a signature identification approach which is based on using dynamic information of signature video. It composes of four stages. First, the foreground image is extracted. Second the signature shape is obtained by detecting and tracking the pen tip in each frame. The pen tip detection error rate is decreased using a proposed modification. Third, some features based on energy motion image are calculated. At the last stage, the signature model is formed which is used in signature identification procedure. We have generated a signature video database of 50 persons to evaluate the proposed method. The number of 13 signatures of each person are used for training. In addition 8 genuine and 8 fake signatures are used for testing purposes. The Accuracy and Equal Error Rate measures areobtained as 95.02% and 3.8% respectively