Title :
From Template to Image: Reconstructing Fingerprints from Minutiae Points
Author :
Ross, Arun ; Shah, Jidnya ; Jain, Anil K.
Author_Institution :
Lane Dept. of Comput. Sci. & Electr. Eng., West Virginia Univ., Morgantown, WV
fDate :
4/1/2007 12:00:00 AM
Abstract :
Most fingerprint-based biometric systems store the minutiae template of a user in the database. It has been traditionally assumed that the minutiae template of a user does not reveal any information about the original fingerprint. In this paper, we challenge this notion and show that three levels of information about the parent fingerprint can be elicited from the minutiae template alone, viz., 1) the orientation field information, 2) the class or type information, and 3) the friction ridge structure. The orientation estimation algorithm determines the direction of local ridges using the evidence of minutiae triplets. The estimated orientation field, along with the given minutiae distribution, is then used to predict the class of the fingerprint. Finally, the ridge structure of the parent fingerprint is generated using streamlines that are based on the estimated orientation field. Line integral convolution is used to impart texture to the ensuing ridges, resulting in a ridge map resembling the parent fingerprint. The salient feature of this noniterative method to generate ridges is its ability to preserve the minutiae at specified locations in the reconstructed ridge map. Experiments using a commercial fingerprint matcher suggest that the reconstructed ridge structure bears close resemblance to the parent fingerprint
Keywords :
convolution; fingerprint identification; image matching; image reconstruction; fingerprint matcher; fingerprint reconstruction; fingerprint-based biometric systems; friction ridge structure; line integral convolution; minutiae distribution; minutiae points; minutiae template; minutiae triplets; noniterative method; orientation estimation algorithm; orientation field information; Biometrics; Convolution; Fingerprint recognition; Fingers; Friction; Image databases; Image matching; Image reconstruction; Neurons; Security; Fingerprints; fingerprint reconstruction; line integral convolution; minutiae; security; streamlines.; templates; Algorithms; Artificial Intelligence; Biometry; Dermatoglyphics; Fingers; Humans; Image Interpretation, Computer-Assisted; Pattern Recognition, Automated; Reproducibility of Results; Sensitivity and Specificity; Signal Processing, Computer-Assisted;
Journal_Title :
Pattern Analysis and Machine Intelligence, IEEE Transactions on
DOI :
10.1109/TPAMI.2007.1018