Showing papers by "Nalini K. Ratha published in 2004"

System and method for remote self-enrollment in biometric databases

Abstract: A method and system is provided to provide enrollment of biometric data from individuals without the need for the enrollees to travel to a central location. The system and method provides for optionally detecting multiple types of biometric data, for example, fingerprints, facial scan, visual scan, iris scan, voice scan, or the like, to be captured at the point of enrollee use. During the biometric capture process, the biometric enrollment device monitors and establishes the identity of the enrollee and measures the quality of the biometric input as it occurs. If unacceptable quality is detected, then repeated biometric scans may be necessary, but is done at time of enrollment avoiding any need to send inaccurate information back to a service institution. When the enrollment process completes, the biometric data is encrypted, time stamped and either mailed back to the service institution or is transmitted back. The biometric device may remain with the user for subsequent use as an identification sensor which may authenticate a user with stored biometric information to authenticate a user's identity for a transaction or a request to access a service or equipment. The biometric enrollment device may also be embodied with another piece of equipment to authenticate use of that equipment.

Fingerprint biometric machine representations based on triangles

Abstract: There is provided an apparatus, method, and program storage device for representing biometrics. The apparatus includes a biometric feature extractor and a transformer. The biometric feature extractor is for extracting features corresponding to a biometric depicted in an image, and for defining one or more sets of one or more geometric shapes by one or more of the features. Each of the one or more geometric shapes has one or more geometric features that is invariant with respect to a first set of transforms applied to at least a portion of the image. The transformer is for applying the first set of transforms to the at least a portion of the image to obtain one or more feature representations that include one or more of the one or more geometric features, and for applying a second set of transforms to the one or more feature representations to obtain one or more transformed feature representations.

Iris individuality: a partial iris model

Abstract: Biometrics-based personal authentication systems are becoming popular with increased demand on security. A biometrics is expected to have significant amount of discriminatory information in representing uniqueness of a person. This discriminatory information about the biometric is loosely defined as the individuality. Even though some individuality studies have been carried out for fingerprints, face and handwriting, formal analysis of iris individuality has not been carried out. We propose a partial model for iris individuality and show its usefulness in predicting the empirical performance results.

A Secure Protocol for Data Hiding in Compressed Fingerprint Images

Abstract: Data hiding techniques can be employed to enhance the security of biometrics-based authentication systems. In our previous work, we proposed a method to hide challenge responses in a WSQ-compressed fingerprint image. In this paper, we extend the work to analyze the security holes in the data hiding method and enhance the hiding technique to thwart attacks on the system. We employ several proven IT security techniques to provide a secure method of hiding responses in fingerprint images. The technique presented here can be used in hiding responses in other biometrics with minor changes to suit the domain.

Dynamic behavior analysis in compressed fingerprint videos

Abstract: Traditional fingerprint acquisition is limited to single-image capture and processing. With the advent of faster capture hardware, faster processors, and advances in video compression standards, newer systems can capture and exploit video signals for tasks that are difficult using a single image. We propose the use of fingerprint video sequences to investigate detecting two aspects of the dynamic behavior of fingerprints. Specifically, we are interested in the detection of distortion of fingerprint impressions due to excessive force and the detection of the positioning of fingers during image capture. These issues often lead to difficulties in establishing a precise match between acquired images. The proposed techniques investigate dynamic characteristics of fingerprints across video sequence frames. A significant advantage of our approach for distortion analysis is that it works directly on MPEG-1,-2 encoded fingerprint video bitstreams. The proposed methods have been tested on the NIST-24 live-scan fingerprint video database and the results are promising. We also describe a new concept called the "resultant biometrics", a new type of biometrics which has both a physiological, physical (e.g., force, torque, linear motion, rotation) component and/or a temporal characteristic, added by a subject to an existing biometric. This resultant biometric is both desirable and efficient in terms of easy modification of compromised biometrics and is harder to produce with spoof body parts.

Performance evaluation in 1: 1 biometric engines

Abstract: Performance of a biometric system is characterized by its speed, accuracy, and cost This paper presents fundamentals of 1 : 1 biometric match engine accuracy performance metrics and its evaluation Here, we explain the basic terminology, performance metrics and related system issues We also discuss practical methods used for evaluating 1 : 1 biometric match engine accuracy performance and provide a summary of the state-of-art of biometric identifier accuracies.

An evaluation of error confidence interval estimation methods

Abstract: Reporting the accuracy performance of pattern recognition systems (e.g., biometrics ID system) is a controversial issue and perhaps an issue that is not well understood. This work focuses on the research issues related to the oft used confidence interval metric for performance evaluation. Using a biometric (fingerprint) authentication system, we estimate the false reject rates and false accept rates of the system using a real fingerprint dataset. We also estimate confidence intervals of these error rates using a number of parametric and non-parametric (e.g., bootstrapping) methods. We attempt to assess the accuracy of the confidence intervals based on estimate and verify strategy applied to repetitive random train/test splits of the dataset. Our experiments objectively verify the hypothesis that the traditional bootstrap and parametric estimate methods are not very effective in estimating the confidence intervals and magnitude of interdependence among data may be one of the reasons for their ineffective estimates. Further, we demonstrate that the resampling the subsets of the data samples (inspired from moving block bootstrap) may be one way of replicating interdependence among the data; the bootstrapping methods using such subset resampling may indeed improve the accuracy of the estimates. Irrespective of the method of estimation, the results show that the (1-/spl alpha/) 100% confidence intervals empirically estimated from the training set capture significantly smaller than (1-/spl alpha/) fraction of the estimates obtained from the test set.

Large-Scale Applications

Abstract: Biometric identifiers, systems, and databases are really put to the test when 1:many searches of large biometric databases are part of the enrollment policy or authentication protocol. In such identification problems, not only are low error rates desired, high 1:1 match rates are quite often also required.

Dynamic Behavior in Fingerprint Videos

Abstract: Traditional fingerprint acquisition is limited to a single image capture and processing. With the advent of faster capture hardware, faster processors, and advances in video compression standards, newer systems capture and exploit video signals for tasks that are difficult using single images. In this chapter, we propose the use of fingerprint video sequences to investigate dynamic behaviors of fingerprints across multiple frames. In particular, we present a novel approach to detect and estimate distortion occurring in compressed fingerprint video streams. Our approach directly works on MPEG-{1,2} encoded fingerprint video bitstreams to estimate interfield flow without decompression and uses this flow information to investigate temporal characteristics of the behaviors of the fingerprints. The joint temporal and motion analysis leads to a novel technique to detect and characterize distortion reliably. The proposed method has been tested on the NIST-24 database, and the results are very promis ing. We also describe a new concept called the “resultant biometrics”—a new type of biometrics that has both a physiological, physical (e.g., force, torque, linear motion, rotation) component and/or temporal characteristic, added by a subject to an existing biometrics. This resultant biometric is both desirable and efficient in terms of easy modification of compromised biometrics and is harder to produce with spoof body parts.

Creating and Maintaining Databases

Abstract: Biometric enrollment is a serious biometric research topic because it asks an individual to give out even more private information (e.g., fingerprint) about his or herself. However, enrollment is just a process directed by some enrollment policy. This policy needs to be acceptable to the public, since (almost by definition) policies are public documents and at least must be understood by the public. Obviously, part of the enrollment process should be a clear statement of how, where, and when this private information will be used.

The Common Biometrics

Abstract: In this chapter we provide a brief description of the six most widely used (or widely discussed) biometrics. These most commonly used automated biometric identifiers are (i) finger, (ii) face, (iii) voice (speaker recognition), (iv) hand geometry, (v) iris, and (vi) signature. Chapter 4 describes other biometrics that are not currently as common.

Authentication and Biometrics

Abstract: Biometrics is often used for establishing trusted communication between two parties to negotiate access to an application. This is also a topic that has been studied in the field of information security for quite a while now. Therefore, in the next sections we introduce some security terms and tools that can be found, for example, in [109,162,208]. Indeed we take the liberty of following Chapter 4 of [162] fairly closely.