A Novel Approach To Classification Based FingerPrint Verification System

Fingerprints are the most oftenly used biometric feature for a person credentials and verification in the field of biometric identification. Fingerprints possess two main types of features that are used for automatic fingerprint identification and verification. First is the Ridge and Furrow structure that forms a special pattern in the central region of the fingerprint and second is the Minutiae details which is associated with the local ridge and furrow structure.In this paper, we have concentrated our implementation on Minutiae based method followed by the discussion about the implementation of a minutiae based matching technique. This approach has been intensively studied, and also is the backbone of the current available fingerprint recognition products. In particular we are interested only in two of the most important minutia features i.e. Ridge Ending and Ridge bifurcation. In a traditional biometric recognition system, the biometric template is usually stored on a central server during enrollment. The candidate biometric template captured by the biometric device is sent to the server where the processing and matching steps are performed. This paper presents an approach to speed up the matching process by classifying the fingerprint pattern into different groups at the time of enrollment, and improves fingerprint matching while matching the input template with stored template. To solve the problem, we take several aspects into consideration like classification of fingerprint, singular points etc. The algorithm result indicates that this approach manages to speed up the matching effectively, and therefore proves to be suitable for large database like forensic divisions.