This paper develops a new approach to understand and measure variations in biometric sample quality. We begin with the intuition that degradations to a biometric sample will reduce the amount of identi able information available. In order to measure the amount of identi able information, we de ne

The impact of using different lossless compression algorithms on the compression ratios and timings when processing various biometric sample data is investigated. In particular, we relate the application of lossless JPEG, JPEG-LS, lossless JPEG2000 and SPIHT, PNG, GIF, and a few general purpose

The evaluation of biometric sample quality is of great importance in the evaluation of biometric algorithms. In this paper, we propose a novel hierarchical model to compute the sample quality at three levels. This model is developed on the basis of three types of influencing factors: global factors

include appropriateness to the experimental design, a corpus size large enough to allow statistically rigorous characterization of results, and the availability of comprehensive metadata that allow inferences to be made on various data set attributes. In this paper, we review a ten-year biometric sampling

Abstract. This paper addresses the problem of evaluating the quality of handwritten signatures used for biometric authentication. It is shown that some signature samples yield significantly worse performance than other samples from the same person. Thus, the importance of good reference samples

Biometric systems are designed to identify a person based on physiological or behavioral characteristics. In order to predict the utility of a particular image for identification, there is an interest in measures to calculate the biometric image quality. Such measures often assume (implicitly

′ , if and only if the identities ω and ω ′ are close to each other as measured by the “set overlap ” distance metric. A Fuzzy IBE scheme can be applied to enable encryption using biometric inputs as identities; the error-tolerance property of a Fuzzy IBE scheme is precisely what allows for the use of biometric

using iris samples from 70 different eyes, with 10 samples from each eye. We found that an error-free key can be reproduced reliably from genuine iris codes with a 99.5 percent success rate. We can generate up to 140 bits of biometric key, more than enough for 128-bit AES. The extraction of a repeatable

Abstract—We document methods for the quantitative evaluation of systems that produce a scalar summary of a biometric sample’s quality. We are motivated by a need to test claims that quality measures are predictive of matching performance. We regard a quality measurement algorithm as a black box

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