With the introduction of biometrics technology which is an advanced computer technique now
widely adopted as a front line security measure for both identity verification and crime detection,
and also others an effective crime deterrent. In an increasingly digital world, reliable personal
authentication has become an important human computer interface activity. Fingerprint
recognition could be very complex pattern recognition problem. It is difficult to design accurate
algorithms that are capable of extracting prolific features and comparing them in a robust way,
especially in poor quality fingerprint images and when low-cost acquisition devices with small
area are adopted. There is a greatest misconception that the fingerprint recognition is a fully
solved problem considering it was one of the first applications of all amongst machine pattern
recognition. A fingerprint is the feature pattern on the finger. It is proved through strong
evidences that each fingerprint is almost unique in nature. Each individual retains his own
fingerprints with the permanent and durable uniqueness. Hence fingerprints are being adapted for
identification and forensic investigation. The fingerprint recognition problem can be grouped
into two sub-categories: one is termed as fingerprint verification and while the other is termed as
fingerprint identification. Additionally, apart from the manual approach of fingerprint
recognition by the experts, fingerprint recognition here is usually referred as AFRS (Automatic
Fingerprint Recognition System), which is drastically program-based. The proposed system
presents the variation of Fast Fourier Transform on finger print recognition by fast fingerprint
minutiae extraction and recognition algorithm that improves the clarity between the ridge and
valley structures of the supposed to be provided finger print images in accordance with the
frequency as well as the orientation of the local ridges and extracting correct minutiae.