Fingerprints are not compared and also not stored in the database as bitmap images. Fingerprint matching techniques can be placed into two categories: minutiae-based and correlation based. Minutiae points are first found and then mapped to the relative index of the finger in minutiae-based technique.
The most common type of fingerprint patterns is loop and it account almost 65% of the matches and is as shown below.
The arch pattern is a more open curve than the loop. There are two different models of these particular arch patterns: they are the “plain arch and tended arch patterns”
“This particular pattern occurs almost 30% fingerprints and are defined by atleast one ridge that composes a complete circle and is as shown below”
It is not always sure that fingerprint ridges are straight and continuous
always. They can be broken, forked and changed directionally. The points where the ridges end or broken are called minutiae points and these points are the main key for unique identification. Ridge endings and ridge bifurcations are the two most important types of ridge points and are as shown below
The most important factor the decision speed mainly depends on few items like the level of security implemented and answers that were delivered in the sense negative answers will affect the speed than the positive answers any more. The speed and the accuracy algorithms are no way dependent on each other. The minutiae found on many fingerprint samples are stored for future comparison studies. Encoding and other compression techniques are also applied on minutiae samples found. In general the typical and traditional formal size of these particular master templates would be around between 24 bytes and one kilobyte. A very huge set of these desired data is stored in the fingerprints captured. Due to the heavy level of data that is present in any single fingerprint the probability of resulting a wrong match is always less and can be reduced to a very small fraction. These fingerprint technologies can also be targeted and more better ways can be implemented to achieve these targets on a very large databases.
To obtain the accurate results from the fingerprints, there are some pre-processor techniques and steps to be followed and few of them are as below