Fingerprint matching using ridges
Pattern Recognition
Privacy-preserving multimodal person and object identification
Proceedings of the 10th ACM workshop on Multimedia and security
A hybrid swipe fingerprint mosaicing scheme
AVBPA'05 Proceedings of the 5th international conference on Audio- and Video-Based Biometric Person Authentication
| Hi-index | 0.00 |
Although the problem of automatic fingerprint matching has been extensively studied, it is nevertheless, not a fully solved problem. In this thesis, an information fusion approach is adopted to address some of the limitations of existing fingerprint matching systems. A hybrid fingerprint system that utilizes both minutiae points and ridge feature maps to represent and match fingerprint images has been developed. The hybrid matcher is shown to perform significantly better than a traditional minutiae-based matcher. The ridge feature maps extracted by this technique have also been used to align and register fingerprint image pairs via a correlation process, thereby obviating the need to rely on minutiae points for image registration. To address the problem of partial prints obtained from small-sized sensors, a fingerprint mosaicking scheme has been developed. The proposed technique constructs a composite fingerprint template from two partial fingerprint impressions by using the iterative control point (ICP) algorithm that determines the transformation parameters relating the two impressions. To mitigate the effect of non-linear distortions in fingerprint images on the snatching process, an average deformation model has been proposed. The model is developed by comparing a fingerprint impression with several other impressions of the same finger and observing the common ridge points that occur in them. An index of deformation has been suggested in this context to aid in the selection of an ‘optimal’ fingerprint impression from a set of impressions. Finally, techniques to combine fingerprint information with the other biometric traits of a subject (viz., face and hand geometry) are presented. To enhance user convenience, a learning methodology has been used to compute user-specific parameters in a multibiometric system. Information fusion systems, as presented in this thesis, are expected to be more reliable and robust than systems that rely on a single source of information.