Fingerprint is most popular and common biometric trait used for authentication. The fingerprint is a physiological biometric characteristic to identify person. Fingerprint recognition is the problem of searching a fingerprint in the reference database to find a fingerprint that matches a given fingerprint. For enhancing the performance and accuracy of biometric fingerprint recognition system on...

We present a deep artificial neural network (DANN) model that learns latent fingerprint image patches using a stack of Restricted Boltzmann Machines (RBMs), and uses it to perform segmentation of latent fingerprint images. Artificial neural networks (ANN) are biologically-inspired architectures that produce hierarchies of maps through learned weights or filters. Latent fingerprints are fingerpr...

Minutiae-based representation is the most widely adopted fingerprint representation scheme. The compactness of minutiae template has created an impression that the minutiae template does not contain sufficient information to allow the reconstruction of the original fingerprint image. This belief has now been shown to be false; several algorithms have been proposed that can reconstruct fingerpri...

In this paper we study that fingerprints are the oldest and most widely used form of biometric identification. The widespread use of fingerprints, there is little statistical theory on uniqueness of fingerprint minutiae. A critical step in study statistics of fingerprint minutiae is to reliably extract minutiae from the fingerprint images. Automatic and reliable extraction of minutiae from the ...

Fingerprint identification and verification are one of the most significant and reliable identification methods. It is impossible that two people have the same fingerprint. Automatics identification of humans based on fingerprint requires the input fingerprint to be match with a large number of fingerprints in the database. Generally, the fingerprint recognition systems are unable to solve the ...

The performance of an automatic fingerprint verification approach relies heavily on the quality of the fingerprint image. Enhancement of the fingerprint image is then a crucial step in automatic fingerprint verification. This paper discusses the fingerprint image processing methods for automatic verification and proposes an adaptive oriented low pass filter to enhance the fingerprint image qual...

OBJECTIVES To determine the prevalence of fingerprint verification failure and to define and quantify the fingerprint changes associated with fingerprint verification failure. DESIGN Case-control study. SETTING Referral public dermatology center. PATIENTS The study included 100 consecutive patients with clinical hand dermatitis involving the palmar distal phalanx of either thumb and 100 a...

Fingerprint image quality is an important factor in the performance of Automatic Fingerprint Identification Systems(AFIS). It is used to evaluate the system performance, assess enrollment acceptability, and evaluate fingerprint sensors. This paper presents a novel methodology for fingerprint image quality measurement. We propose limited ring-wedge spectral measure to estimate the global fingerp...

A critical step in automatic fingerprint matching is to automatically and reliably extract minutiae from the input fingerprint images. However, the performance of a minutiae extraction algorithm relies heavily on the quality of the input fingerprint images. In order to ensure that the performance of an automatic fingerprint identification/verification system will be robust with respect to the q...

Automatic Fingerprint Identification System (AFIS) uses fingerprint segmentation as its pre-processing step. A fingerprint segmentation step divides the fingerprint image into foreground and background. An AFIS that uses a feature extraction algorithm for person identification will tend to fail if it extracts spurious features from the noisy background area. So fingerprint image segmentation pl...