Natalia A. Schmid

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The popularity of the iris biometric has grown considerably over the past two to three years. Most research has been focused on the development of new iris processing and recognition algorithms for frontal view iris images. However, a few challenging directions in iris research have been identified, including processing of a nonideal iris and iris at a(More)
Iris recognition, the ability to recognize and distinguish individuals by their iris pattern, is the most reliable biometric in terms of recognition and identification performance. However, performance of these systems is affected by poor quality imaging. In this work, we extend previous research efforts on iris quality assessment by analyzing the effect of(More)
Practical iris-based identification systems are easily accessible for data collection at the matching score level. In a typical setting, a video camera is used to collect a single frontal view image of good quality. The image is then preprocessed, encoded, and compared with all entries in the biometric database resulting in a single highest matching score.(More)
Iris biometric is one of the most reliable biometrics with respect to performance. However, this reliability is a function of the ideality of the data. One of the most important steps in processing nonideal data is reliable and precise segmentation of the iris pattern from remaining background. In this paper, a segmentation methodology that aims at(More)
In the selection of biometrics for use in a recognition system and in the subsequent design of the system, the predicted performance is a key consideration. The realizations of the biometric signatures or vectors of features extracted from the signatures can be modeled as realizations of random processes. These random processes and the resulting(More)
In the field of iris-based recognition, evaluation of quality of images has a number of important applications. These include image acquisition, enhancement, and data fusion. Iris image quality metrics designed for these applications are used as figures of merit to quantify degradations or improvements in iris images due to various image processing(More)
Natalia A. Schmid, Yoram Bresler, and Pierre Moulin University of Illinois at Urbana-Champaign Coordinated Science Laboratory, 1308 West Main, Urbana, IL 61801 nschmid, ybresler, moulin ABSTRACT We consider the estimation of an unknown arbitrary 2D object shape from sparse noisy samples of its Fourier transform. The(More)
The popularity of iris biometric has grown considerably over the past two to three years. It has resulted in the development of a large number of new iris encoding and processing algorithms. Since there are no publicly available large-scale and even medium-size data bases, neither of the newly designed algorithms has undergone extensive testing. The(More)
In this paper, we describe a face video database, UTK-LRHM, acquired from long distances and with high magnifications. Both indoor and outdoor sequences are collected under uncontrolled surveillance conditions. To our knowledge, it is the first database to provide face images from long distances (indoor: 10–16 m and outdoor: 50–300 m). The corresponding(More)