Automatic fingerprint classification provides an important indexing scheme to facilitate efficient matching in large-scale fingerprint databases in Automatic Fingerprint Identification Systems (AFISs). The paper presents a new fast fingerprint classification module implementing on embedded Weightless Neural Network (RAM-based neural network). The proposed WNN architecture uses directional maps ...

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...

Indoor location estimation, the process of reckoning the location of a device in an indoor environment, remains a technical challenge due to the poor performance of GPS in such settings. While a substantial amount of work has been done in this context, particularly employing the Wi-Fi fingerprinting technique, the very approach has certain shortcomings. A major limitation is the need of time-an...

A growing demand for the information about location of numerous devices in indoor and urban environments raises the need for indoor localization. Indoor localization is needed for various applications and services, and it is considered as one of the key enablers of the Future Internet concepts. One of the most promising approaches in indoor localization is fingerprinting using information from ...

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...

In this study, the authors present a hierarchical algorithm to register a partial fingerprint against a full fingerprint using only the orientation fields. In the first level, they shortlist possible locations for registering the partial fingerprint in the full fingerprint using a normalised correlation measure, taking various rotations into account. As a second level, on those candidate locati...

The market of localization based service (LBS) is expanding. The acquisition of physical location is the fundamental basis for LBS. GPS, the de facto standard for outdoor localization, does not work well in indoor environment due to the blocking of signals by walls and ceiling. To acquire high accurate localization in indoor environment, many techniques have been developed. The vision based loc...