A blind system identification approach to cancelable fingerprint templates. (June 2016) - Wang, Song; Hu, Jiankun
Abstract: Cancelable biometrics is an important biometric template protection scheme. With no a priori image pre-alignment, alignment-free cancelable fingerprint templates do not suffer from inaccurate singular point detection. In this paper, we develop a blind system identification approach to the design of alignment-free cancelable fingerprint templates. The binary string, derived from quantized pair-minutiae vectors, is to be secured and its frequency samples act as the input to the proposed algorithm. Motivated by the identifiability of the source signal in blind system identification, we propose to protect the binary string׳s frequency samples, which are treated as the source input, by countering or dissatisfying the identifiability condition so that they cannot be recovered from the output complex vector (transformed template). The proposed transform is irreversible because when the identifiability condition is not met, non-identification of the source input is theoretically guaranteed in blind system identification. Security, matching performance and resource requirement are the main factors in cancelable template design. With the size of the transform parameter key and transformed templates being moderate, the proposed method suits resource-limited applications, e.g., smartcards, driver license and mobile phones. Evaluation of the proposed method over FVC2002 DB1, DB2 and DB3 shows that the new method exhibits favorable performance compared to state-of-the-art alignment-free cancelable fingerprint templates. Abstract : Highlights: Design of alignment-free cancellable fingerprint templates. Proposed cancellable templates satisfying the requirements of non-invertibility, revocability and diversity. Non-invertible transform to guarantee non-identification of the frequency samples of the binary string. Proposed method suitable for resource-limited applications, e.g., smardcards, driver license and mobile phones. Satisfactory matching performance compared with the existing alignment-free cancellable fingerprint templates.