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Zhe Jin, Bok-Min Goi, Andrew Teoh and Yong Haur Tay A two-dimensional random projected minutiae vicinity decomposition-based cancellable fingerprint template Security and Communication Networks 7

Version of Record online: 19 AUG 2013 | DOI: 10.1002/sec.865

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We proposed a two-dimensional random projected minutiae vicinity decomposition (MVD) method, which projects the MVD features into random space using a random matrix derived from user-specific token. Thus, the non-invertible property is significantly enhanced over the solely MVD-based representation. The experimental results show that the proposed method is not only excelled in recognition accuracy but also complying with cancellability, diversity, and non-invertibility. Remarkably, a good preservation of MVD neighborhood structure by random projection is exploited and reported.

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