Minutiae data synthesis for fingerprint identification applications
In this paper, we address the false rejection problem due to the small solid state sensor area available for fingerprint image capture. We propose a minutiae data synthesis approach to circumvent this problem. The main advantages of this approach over the existing image mosaicing approach include low memory storage requirements and low computational complexity. Moreover, the possible matching search overhead due to data redundancy can be reduced. Extensive experiments are 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.