Fingerprint mosaicking
It has been observed that the reduced contact area offered by solid-state fingerprint sensors does not provide sufficient information (e.g., number of minutiae) for high accuracy user verification. Further, multiple impressions of the same finger acquired by these sensors, may have only a small region of overlap thereby degrading the matching performance of the verification system. To deal with this problem, we have developed a fingerprint mosaicking scheme that constructs a composite fingerprint template using multiple impressions. A composite template reduces storage, improves matching time and alleviates the problem of template selection. In the proposed algorithm, two impressions (templates) of a finger are initially aligned using the corresponding minutiae points. This alignment is used by a modified version of the well-known iterative closest point algorithm (ICP) to compute a transformation matrix that defines the spatial relationship between the two impressions. The resulting transformation matrix is used in two ways: (a) the two templates are stitched together to generate a composite image. Minutiae points are then detected in this composite image; (b) the minutia maps obtained from each of the individual impressions are integrated to create a larger minutia map. Our experiments show that a composite template improves the performance of the fingerprint matching system by ∼ 4%.