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This paper proposes a novel fingerprint enhancement algorithm based on contextual filtering in DCT domain. All intrinsic fingerprint features including ridge orientation and frequency are estimated simultaneously from DCT analysis, resulting in fast and efficient implementation. In addition, the proposed approach takes advantage of frequency-domain enhancement resulting in best performance in high curvature area. Comparing with DFT domain, DCT has better signal energy compaction and perform faster transform with real coefficients. Moreover, the experimental results show that the DCT approach is out-performed the traditional Gabor filtering, including the fastest separable Gabor filter, in both quality and computational complexity.

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