Enhanced Cancelable Biometrics for Online Signature Verification

Cancelable approaches for biometric person authentication have been studied to protect enrolled biometric data, and several algorithms have been proposed. One drawback of cancelable approaches is that the performance is inferior to that of non-cancelable approaches. In this paper, we propose a scheme to improve the performance of a cancelable approach for online signature verification. Our scheme generates two cancelable dataset from one raw dataset and uses them for verification. Preliminary experiments were performed using a distance-based online signature verification algorithm. The experimental results show that our proposed scheme is promising.