Enhancing Security and Privacy in Biometric Cryptosystems for Trusted Authentication

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In this paper, the authors introduces a novel fingerprint matching algorithm using both ridge features and the conventional minutiae features to increase the recognition performance against non-linear deformation in fingerprints. The proposed ridge features are composed of four elements: ridge count, ridge length, ridge curvature direction and ridge type. These ridge features have some advantages in that they can represent the topology information in entire ridge patterns existing between two minutiae and not changed by nonlinear deformation of the finger. For extracting ridge features, they also define the ridge-based coordinate system in a skeletonized image. With the proposed ridge features and conventional minutiae features (minutiae type, orientation and position), they propose a novel matching scheme using a breadth-first search to detect the matched minutiae pairs incrementally.