ABSTRACT

Fingerprints are being extensively used for person identification in a number of commercial, civil, and forensic applications. The current Fingerprint matching technology is quite mature for matching full prints, matching partial fingerprints still needs lots of improvement. Most of the current fingerprint identification systems utilize features that are based on minutiae points and ridge patterns. The major challenges faced in partial fingerprint matching are the absence of sufficient minutiae features and other structures such as core and delta. However, this technology suffers from the problem of handling incomplete prints and often discards any partial fingerprints obtained. Recent research has begun to delve into the problems of latent or partial fingerprints. In this paper we present a novel approach for partial fingerprint matching scheme based on SIFT (Scale Invariant Feature Transform) features and matching is achieved using a modified point matching process. Using Neurotechnology database, we demonstrate that the proposed method exhibits an improved performance when matching full print against partial print .