Long digital straight segments for fingerprint matching

In this paper, we proposed a new feature extraction method for fingerprint matching. We find that long digital straight segments (LDSSs) in fingerprints can accurately characterize the global structure of fingerprints. Besides, the orientation information of these segments is more stable compared to orientation fields. It is a useful information for representing the fingerprints. In addition, each digital straight segment can be represented by four parameters: x-coordinate, y-coordinate, slope and length. It only needs about 600 bytes to store all the parameters of LDSSs of a fingerprint, which is much less than the storage orientation field needs. Finally, the LDSSs can automatically capture the maximum structural information of local regions. Consequently, LDSSs are more convenient to combine with the minutiae based methods than orientation fields. The experiments conducted on fingerprint database FVC2002 DB3a and DB4a show that our method is effective.