An efficient method for partial fingerprint recognition based on local binary pattern

Matching of partial fingerprints has important applications in both biometrics and forensics. It is well-known that the accuracy of minutiae-based matching algorithms dramatically decreases as the number of available minutiae decreases. When singular structures such as core and delta are unavailable, extended features can be utilized. The current Fingerprint matching technology is quite mature for matching tenprints, matching partial fingerprints still needs lots of improvement. The major challenges faced in partial fingerprint matching are the absence of sufficient level 2 features (minutiae) and other structures such as core and delta. Thus common matching methods based on alignment of singular structures would fail in case of partial prints. Pores (level 3 features) on fingerprints have proven to be discriminative features and have recently been successfully employed in automatic fingerprint recognition systems (AFRS). This paper presents suitable technique for partial fingerprint matching based on pores corresponding their Local Binary Pattern (LBP) features. The first step involves extracting the pores from the partial image. These pores act as anchor points and sub window (32*32) is formed surrounding the pores. Then rotation invariant LBP histograms are obtained from the surrounding window. Finally chisquare formula is used to calculate the minimum distance between two histograms to find best matching score. The experimental results are demonstrated on NIST SD30 database and shows high matching score when matching partial with full fingerprint database.