An efficient approach for partial fingerprint recognition based on Pores and SIFT features using fusion methods

Abstract

Biometrics has come to occupy an increasingly important role in human identification due primarily to their universality and uniqueness. As a result of this evolution, a new breed of techniques and methods for user identity recognition and verification has appeared based on the biometric features that are unique to each individual. Examples of common biometrics used include iris, DNA, voice patterns, facial patterns and fingerprint. Out of this, the fingerprint is a more popular biometric modality and has been used for personal identification for more than 100 years. The popularity is due to the fact that fingerprints never change and no two fingerprints are similar. It has been proven that even identical twins have different fingerprints. Because of these newlinedesirable properties, automated systems for Automatic Fingerprint Identification and Authentication System (AFIS) have been developed and over the years this interest has increased steadily. Although fingerprint matching based on minutiae features is a well researched problem in the field of AFIS, it can achieve very high accuracy given fingerprint images are same size or covering sufficiently large fingerprint areas, its accuracy is still far from being satisfactory when partial fingerprint images are available. While the introduction of compact silicon chip-based sensors that capture only part of the fingerprint has made this problem important from a commercial perspective and partial fingerprints obtained at crime scenes, there is also considerable interest in processing partial fingerprint matching. The need for recognition of partial fingerprints is increasing in both forensic and civilian applications. newline