Reconstruction and Matching of Fingerprint from Minutiae to Image
FINGERPRINTS are ridge and valley patterns present, on the surface of human fingertips. The set of minutia points is widely used in fingerprint matching and fingerprint representation. To reconstruct the original fingerprint image from which minutiae were extracted, it was believed that the minutiae set do not contain sufficient information. To reconstruct fingerprint images from their minutiae representations, recent studies have shown that it is indeed possible. Improving the template interoperability, and improving fingerprint synthesis, reconstruction techniques demonstrate the need for securing fingerprint templates. The need for securing fingerprint templates, improving the template interoperability, and improving fingerprint synthesis, Reconstruction techniques demonstrate. The matching performances obtained from original fingerprint images and reconstructed fingerprint images there is there is a large gap between the matching performance fingerprint images. To improve the fingerprint reconstruction, the prior knowledge about fingerprint ridge structures is encoded in terms of orientation patch and continuous phase patch dictionaries. While the continuous phase patch dictionary is used to reconstruct the ridge pattern, the orientation patch dictionary issued to reconstruct the orientation field from minutiae. Experimental results on three public domain databases demonstrate that the proposed reconstruction algorithm outperforms the state-of-the-art reconstruction algorithms with respect to type-I attack (matching the reconstructed fingerprint against the same impression from which minutiae set was extracted) and type-II attack (matching the reconstructed fingerprint against a different impression of the same finger).