From Template to Image: Reconstructing Fingerprints from Minutiae Points

Abstract

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.

Design & Implementation of Fingerprint Biometrics based on Discretized Fingerprint Texture Descriptor

“…There are three types of sensors used. They are optical sensors, ultrasonic sensors and capacitance sensors [15] B.…”

“…All pixels on boundaries of fore ground regions that have at least one background neighbour are taken. Any point that has more than one foreground neighbour is deleted as long as doing so does not locally disconnect the region containing that pixel [15]. Fingerprint Image Segmentation In general, only a Region of Interest is useful to be recognized for each fingerprint image.…”

FM Model Based Fingerprint Reconstruction from Minutiae Template

“…In other words, minutiae extraction algorithms have been traditionally viewed as a "one-way" transform. Recently, however, this belief has been challenged by some researchers [1][2][3] who were successful in reconstructing a fingerprint image from the given minutiae template.…”

“…A line drawing algorithm was used to generate a sequence of splines passing through the minutiae. Ross et al [2] first estimated the orientation field using selected minutiae triplets in the template. Streamlines were then traced starting from minutiae and border points.…”

“…As a result, SFINGE may generate problematic fingerprints that contain too few minutiae or very long ridges. It is well known that the distribution of minutiae in fingerprints is not random and fingerprints of different pattern types have different minutiae distributions [2]. The minutiae distribution of fingerprints generated by SFINGE may not conform to such distributions since these minutiae are automatically generated during the image filtering process.…”