Biometric quality: a review of fingerprint, iris, and face

Abstract

Biometric systems encounter variability in data that influence capture, treatment, and u-sage of a biometric sample. It is imperative to first analyze the data and incorporate this understanding within the recognition system, making assessment of biometric quality an important aspect of biometrics. Though several interpretations and definitions of quality exist, sometimes of a conflicting nature, a holistic definition of quality is indistinct. This paper presents a survey of different concepts and interpretations of biometric quality so that a clear picture of the current state and future directions can be presented. Several factors that cause different types of degradations of biometric samples, including image features that attribute to the effects of these degradations, are discussed. Evaluation schemes are presented to test the performance of quality metrics for various applications. A survey of the features, strengths, and limitations of existing quality assessment techniques in fingerprint, iris, and face biometric are also presented. Finally, a representative set of quality metrics from these three modalities are evaluated on a multimodal database consisting of 2D images, to understand their behavior with respect to match scores obtained from the state-of-the-art recognition systems. The analysis of the characteristic function of quality and match scores shows that a careful selection of complimentary set of quality metrics can provide more benefit to various applications of biometric quality.

Fingerprint Quality Assessment: Matching Performance and Image Quality

“…Some existing studies propose to calculate correlation between different metrics [4] for comparing the behavior of them. However, this is not completely observable, because there is no explicit linear relation among every group of variant quality metrics.…”

Properties, Functions, Chemical Transformation, Nano-, and Hybrid Materials of Poly(diphenylacetylene)s toward Sensor and Actuator Applications

“…119,120 Biometric identification uses various human physical features and behavioral characteristics such as fingerprints, iris, vein, face, and voice. 121 Among them, fingerprints have been most widely used as bio-information. Our body temperature is maintained near 36.5 C in a normal health state, which is higher than the T m (32.0 C) of octadecane (OD H ).…”

QFuse: Online learning framework for adaptive biometric system

“…It has been shown in literature that quality assessment scores of a biometric sample can be indicative of its recognition performance [33,34,35]. The proposed algorithm computes a quality vector for a given image using computationally inexpensive quality assessment techniques.…”