Abstract
Writing is one of a behavior that can be used for biometric person authentication. A popular modality associated with writing is online signature verification. Online signature verification makes use of a trajectory of pen movement as a feature of writing. Though the trajectory is useful to verify signature, it occupies only a small part of writing features. In this paper, we propose a person authentication method using features extracted from pen holding style, which represents another aspect of writing. The features of pen holding style extracted in this paper are derived from both the hand's behavior and the hand's nature. Pen holding style is captured by a camera, and those features are extracted from the captured image. Dissimilarity scores are calculated from the features, and then combined in score level. In order to evaluate accuracies of proposed pen holding style verification, data from 30 persons are collected. The experimental results show that the proposed algorithm achieves the equal error rate (EER) of 2.7% against others' data, and EER of 4.1% against impersonation data.
