BST Fingerprint Recognition Algorithm follows the commonly accepted fingerprint identification scheme, which uses a set of specific fingerprint feature points ( minutiae ).

However, it contains many powerful algorithmic solutions, which enhance the system performance and reliability. Some of them are listed below:

Image Quality Check Algorithm : This algorithm provides feedback on the quality of the query fingerprint image. It produces error codes such as incorrect image position ( up, down, left, right ); no fingerprint present; or fingerprint too dry or too wet.

Efficient Image Enhancement Algorithm : This algorithm allows to eliminate noises, ridge ruptures and stuck ridges, and extract feature points more reliably even from extremely poor fingerprint images, with processing time of 0.2~0.3 seconds on a Pentium 200.

Fully Tolerant to Fingerprint Distortion and Rotation Matching Algorithm : In usually, there are many distortion, translation, and rotation in query fingerprint image caused by various reasons. BST Fingerprint Recognition Algorithm is fully to them.

BST Fingerprint Engine uses a powerful fingerprint matching algorithm instead of other previous methods, which can match 30,000 fingerprints per second and identify two fingerprints even if they are arbitrarily rotated within 360 ° , translated and have a few same part of image. And then, this algorithm is not dependent on presence of the fingerprint core or delta points in the image.

Fingerprint Enroll Mode with Feature Collection : BST Fingerprint Recognition Engine has the fingerprint enrollment with feature collection mode. This mode generates the collection of the features from 3 fingerprints of the same finger. Each fingerprint image is processed and its feature is extracted. Then these 3 features are analyzed and collected into a single feature collection, which is stored to the database. This way, the enrolled feature is more reliable and system performance considerably increases using this mode.

Database Pre-Sorting by Global Feature Vector : BST Fingerprint Recognition Engine pre-sorts the database entries using the certain global fingerprint feature vector. Fingerprint matching is performed first with the database entries having global feature most similar to those of the query fingerprint image, then the next entries with most similar is matched, and so on, until the matching result is successful or the end of the database is reached. In most cases there is fairly good chance that the correct match will be found already in the beginning of the search. As a result, the number of matching required to achieve fingerprint identification decreases drastically, and correspondingly, the effective matching speed increases.

Suitable Algorithm to 1:1 and 1:N Mode : BST Fingerprint Recognition Engine supports the both 1:1 and 1:N matching mode.