An automated matching technique for fingerprint identification

The purpose of this paper is to demonstrate how a structural matching approach can be used to perform effective rotational invariant fingerprint identification. In this approach, each of the extracted features is correlated with five of its nearest neighbouring features to form a local feature group for a first-stage matching. After that, the feature with the highest match is used as a central feature whereby all the other features are correlated to form a global feature group for a second-stage matching. The correlation between the features is in terms of distance and relative angle. This approach actually make the matching method rotational invariant. A substantial amount of testing was carried out and it shows that this matching technique is capable of matching the four basic fingerprint patterns with an average matching time of 4 seconds on a 66 MHz, 486 DX personal computer.