Minutiae data synthesis for fingerprint identification applications

In this paper, we address the false rejection problem due to small solid state sensor area available for fingerprint image capture. We propose a minutiae data synthesis approach to circumvent this problem. Main advantages of this approach over existing image mosaicing approach include low memory storage requirement and low computational complexity. Moreover, possible matching search overhead due to data redundancy could be reduced. Extensive experiments were conducted to determine the best transformation suitable for minutiae alignment. Among the three transformations presented, affine transformation is found to be most suited for minutiae alignment. We demonstrate the idea of synthesis with an example using physical fingerprint images. The proposed synthesis system is also shown to reduce the number of false rejects caused by the use of different fingerprint regions for matching.