Abstract: Writer verification is a form of biometrics. Among its various approaches, finger-writing
verification of a simple symbol is aimed at being the most convenient, in which a user is verified by
writing a simple symbol with a finger on a smartphone screen. In a previous study, an error rate of
approximately 10 % was achieved. Furthermore, by selecting and fusing individually high-performing features, an equivalent error rate was obtained, even though the number of features used was reduced. In another previous study, we selected features that were resistant to tracing. In this study, we propose new feature selection methods focusing on individuality and independence, and a fusion method that combines them with two conventional selection methods. By using the proposed method, we finally achieved the error rate of approximately 6-7 %.

Keywords: Biometrics, Writer Verification, Finger-writing, Simple Symbol, Feature Selection Fusion.