A Review of Performance Evaluation for Biometrics Systems
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paper_title: The DET curve in assessment of detection task performance

paper_content:

Abstract : We introduce the DET Curve as a means of representing performance on detection tasks that involve a tradeoff of error types. We discuss why we prefer it to the traditional ROC Curve and offer several examples of its use in speaker recognition and language recognition. We explain why it is likely to produce approximately linear curves. We also note special points that may be included on these curves, how they are used with multiple targets, and possible further applications.
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paper_title: Fundamentals of Biometric Authentication Technologies

paper_content:

Biometric authentication technologies are used for the machine identification of individuals. The human-generated patterns used may be primarily physiological or behavioral, but usually contain elements of both components. Examples include voice, handwriting, face, eye and fingerprint identification. In this paper, we look at these technologies and their applications in general, developing a systematic approach to classifying, analyzing and evaluating them. A general system model is shown and test results for a number of technologies are considered.
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paper_title: Fundamentals of Biometric Authentication Technologies

paper_content:

Biometric authentication technologies are used for the machine identification of individuals. The human-generated patterns used may be primarily physiological or behavioral, but usually contain elements of both components. Examples include voice, handwriting, face, eye and fingerprint identification. In this paper, we look at these technologies and their applications in general, developing a systematic approach to classifying, analyzing and evaluating them. A general system model is shown and test results for a number of technologies are considered.
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paper_title: Technical Testing and Evaluation of Biometric Identification Devices

paper_content:

Although the technical evaluation of biometric identification devices has a history spanning over two decades, it is only now that a general consensus on test and reporting measures and methodologies is developing in the scientific community. By “technical evaluation”, we mean the measurement of the five parameters generally of interest to engineers and physical scientists: false match and false non-match rates, binning error rate, penetration coefficient and transaction times. Additional measures, such as “failure to enroll” or “failure to acquire”, indicative of the percentage of the general population unable to use any particular biometric method, are also important. We have not included in this chapter measures of more interest to social scientists, such as user perception and acceptability. Most researchers now accept the “Receiver Operating Characteristic” (ROC) curve as the appropriate measure of the application-dependent technical performance of any biometric identification device. Further, we now agree that the error rates illustrated in the ROC must be normalized to be independent of the database size and other “accept/reject” decision parameters of the test. This chapter discusses the general approach to application-dependent, decision-policy independent testing and reporting of technical device performance and gives an example of one practical test. System performance prediction based on test results is also discussed.
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paper_title: Technical Testing and Evaluation of Biometric Identification Devices

paper_content:

Although the technical evaluation of biometric identification devices has a history spanning over two decades, it is only now that a general consensus on test and reporting measures and methodologies is developing in the scientific community. By “technical evaluation”, we mean the measurement of the five parameters generally of interest to engineers and physical scientists: false match and false non-match rates, binning error rate, penetration coefficient and transaction times. Additional measures, such as “failure to enroll” or “failure to acquire”, indicative of the percentage of the general population unable to use any particular biometric method, are also important. We have not included in this chapter measures of more interest to social scientists, such as user perception and acceptability. Most researchers now accept the “Receiver Operating Characteristic” (ROC) curve as the appropriate measure of the application-dependent technical performance of any biometric identification device. Further, we now agree that the error rates illustrated in the ROC must be normalized to be independent of the database size and other “accept/reject” decision parameters of the test. This chapter discusses the general approach to application-dependent, decision-policy independent testing and reporting of technical device performance and gives an example of one practical test. System performance prediction based on test results is also discussed.
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paper_title: DNA and Destiny: Nature and Nurture in Human Behavior

paper_content:

Genes and Human Behavior The Old Nature versus Nurture Debate The Dark History of Eugenics The Nature of Nurture: Defining Environmental Influences New Tools for an Old Problem New Improvements in the Old Tools The Inheritance of Disease: A Paradigm for the Inheritance of Behavior? Intelligence Mental Disorders Personality Traits Sexual Orientation Alcoholism and Addictive Behavior Crime and Violence Sex, Genes, and Testosterone Biology and Social Responsibility Epilogue References Index
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paper_title: On the similarity of identical twin fingerprints

paper_content:

Reliable and accurate verification of people is extremely important in a number of business transactions as well as access to privileged information. Automatic verification methods based on physical biometric characteristics such as fingerprint or iris can provide positive verification with a very high accuracy. However, the biometrics-based methods assume that the physical characteristics of an individual (as captured by a sensor) used for verification are sufficiently unique to distinguish one person from another. Identical twins have the closest genetics-based relationship and, therefore, the maximum similarity between fingerprints is expected to be found among identical twins. We show that a state-of-the-art automatic fingerprint verification system can successfully distinguish identical twins though with a slightly lower accuracy than nontwins.
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paper_title: The FERET evaluation methodology for face-recognition algorithms

paper_content:

Two of the most critical requirements in support of producing reliable face-recognition systems are a large database of facial images and a testing procedure to evaluate systems. The Face Recognition Technology (FERET) program has addressed both issues through the FERET database of facial images and the establishment of the FERET tests. To date, 14,126 images from 1,199 individuals are included in the FERET database, which is divided into development and sequestered portions of the database. In September 1996, the FERET program administered the third in a series of FERET face-recognition tests. The primary objectives of the third test were to 1) assess the state of the art, 2) identify future areas of research, and 3) measure algorithm performance.
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paper_title: Filterbank-based fingerprint matching

paper_content:

Biometrics-based verification, especially fingerprint-based identification, is receiving a lot of attention. There are two major shortcomings of the traditional approaches to fingerprint representation. For a considerable fraction of population, the representations based on explicit detection of complete ridge structures in the fingerprint are difficult to extract automatically. The widely used minutiae-based representation does not utilize a significant component of the rich discriminatory information available in the fingerprints. Local ridge structures cannot be completely characterized by minutiae. Further, minutiae-based matching has difficulty in quickly matching two fingerprint images containing a different number of unregistered minutiae points. The proposed filter-based algorithm uses a bank of Gabor filters to capture both local and global details in a fingerprint as a compact fixed length FingerCode. The fingerprint matching is based on the Euclidean distance between the two corresponding FingerCodes and hence is extremely fast. We are able to achieve a verification accuracy which is only marginally inferior to the best results of minutiae-based algorithms published in the open literature. Our system performs better than a state-of-the-art minutiae-based system when the performance requirement of the application system does not demand a very low false acceptance rate. Finally, we show that the matching performance can be improved by combining the decisions of the matchers based on complementary (minutiae-based and filter-based) fingerprint information.
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paper_title: Fingerprint recognition in low quality images

paper_content:

Abstract Algorithms are identified which are best suited for an automatic fingerprint recognition system operating on low quality images. New preprocessing algorithms for noise removal and binarization are described. Three approaches to classification are investigated: a correlation classifier, and two feature-based classification schemes. The best results on a database of 80 fingerprints are obtained with spatial-frequency features. Three classifiers (neural net, linear classifier and nearest neighbour) using these features are successful in identifying an independent test set. Details of the results are shown. In conclusion suggestions are made concerning the most suitable algorithms in each of the processing steps.
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paper_title: Surface matching by 3D point's fingerprint

paper_content:

This paper proposes a new efficient surface representation method for the application of surface matching. We generate a feature carrier for the surface point, which is a set of 2D contours that are the projection of geodesic circles onto the tangent plane. The carrier is named point's fingerprint because its pattern is similar to human fingerprint and discriminating for each point. Each point's fingerprint carries the information of the normal variation along geodesic circles. Corresponding points on surfaces from different views are found by comparing fingerprints of the points. This representation scheme includes more local geometry information than some previous works that only use one contour as the feature carrier. It is not histogram based so that it is able to carry more features to improve comparison accuracy. To speed up the matching, we use a novel candidate point selection method based on the shape irregularity of the projected local geodesic circle. The point's fingerprint is successfully used to register both synthetic and real 2 1/2 data.
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paper_title: Biometrical fingerprint recognition: don't get your fingers burned

paper_content:

One of the most critical issues to solve when building multi-accessible systems, such as computer applications, cars or physical buildings, is to determine the identity of a person. A system protecting confidential information, or items of value, puts strong security demands on the identification. Biometry provides us with a userfriendly method for this identification and is becoming a competitor for current identification mechanisms, especially for electronic transactions. However, there are ways to compromise a system based on biometric verification. This article focuses on the drawbacks and risks of biometric verification, specifically verification based on fingerprints. It shows how all currently available fingerprint scanners can be fooled by dummies that are created with very limited means and skills.
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paper_title: Fingerprint Features -- Statistical Analysis and System Performance Estimates

paper_content:

As the need for personal authentication increases, many people are turning to biometric authentication as an alternative to traditional security devices. Concurrently, users and vendors of biometric authentication systems are searching for methods to establish system performance. This paper presents a model that defines the parameters necessary to estimate the performance of fingerprint-authentication systems without going through the rigors of intensive system testing inherent in establishing error rates. The model presented here was developed to predict the performance of the pore-based automated fingerprint-matching routine developed internally in the research and development division at the National Security Agency. This paper also discusses the statistics of fingerprint pores and the efficacy of using pores in addition to the traditionally used minutiae to improve system performance. In addition, this paper links together the realms of automated matching and statistical evaluations of fingerprint features. The result of this link provides knowledge of practical performance limits of any automated matching routine that utilizes pores or minutia features.
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paper_title: Biometrical fingerprint recognition: don't get your fingers burned

paper_content:

One of the most critical issues to solve when building multi-accessible systems, such as computer applications, cars or physical buildings, is to determine the identity of a person. A system protecting confidential information, or items of value, puts strong security demands on the identification. Biometry provides us with a userfriendly method for this identification and is becoming a competitor for current identification mechanisms, especially for electronic transactions. However, there are ways to compromise a system based on biometric verification. This article focuses on the drawbacks and risks of biometric verification, specifically verification based on fingerprints. It shows how all currently available fingerprint scanners can be fooled by dummies that are created with very limited means and skills.
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paper_title: Novel approach to automated fingerprint recognition

paper_content:

The paper describes an enhanced fingerprint recognition system consisting of image preprocessing, feature extraction and matching that runs accurately and effectively on a personal computer platform. The image preprocessing includes histogram equalisation, modification of directional codes, dynamic thresholding and ridgeline thinning which are sufficient to enhance the image to a state ready for feature extraction. Only features extracted are stored in a file for fingerprint matching. The matching algorithm presented is a modification and improvement of the structural approach. Experimental results acquired for matching are accurate, reliable and fast for implementation using a PC and a fingerprint scanner. The proposed fingerprint recognition scheme can provide an efficient way of automated identification and can be extended to numerous other security or administration applications.
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paper_title: The costs and benefits of using complex 2-D Gabor filters in a filter-based fingerprint-matching system

paper_content:

In this paper, we investigate the utility of complex, 2-D Gabor filter for a fingerprint matching system. Previous approaches have used an even symmetric 2-D Gabor filter to perform fingerprint feature extraction processing. Several processing methods using a complex filter are explored and compared to the even-symmetric case. Conclusions are drawn based upon both the results of using a complex filter and the added computational costs of doing so.
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paper_title: FingerCode: a filterbank for fingerprint representation and matching

paper_content:

With the identity fraud in our society reaching unprecedented proportions and with an increasing emphasis on the emerging automatic positive personal identification applications, biometrics-based identification, especially fingerprint-based identification, is receiving a lot of attention. There are two major shortcomings of the traditional approaches to fingerprint representation. For a significant fraction of population, the representations based on explicit detection of complete ridge structures in the fingerprint are difficult to extract automatically. The widely used minutiae-based representation does not utilize a significant component of the rich discriminatory information, available in the fingerprints. The proposed filter-based algorithm uses a bank of Gabor filters to capture both the local and the global details in a fingerprint as a compact 640-byte fixed length FingerCode. The fingerprint matching is based on the Euclidean distance between the two corresponding FingerCodes and hence is extremely fast. Our initial results show identification accuracies comparable to the best results of minutiae-based algorithms published in the open literature. Finally, we show that the matching performance can be improved by combining the decisions of the matchers based on complementary fingerprint information.
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paper_title: On-Line Fingerprint Verification

paper_content:

Fingerprint verification is one of the most reliable personal identification methods. However, manual fingerprint verification is incapable of meeting today's increasing performance requirements. An automatic fingerprint identification system (AFIS) is needed. This paper describes the design and implementation of an online fingerprint verification system which operates in two stages: minutia extraction and minutia matching. An improved version of the minutia extraction algorithm proposed by Ratha et al. (1995), which is much faster and more reliable, is implemented for extracting features from an input fingerprint image captured with an online inkless scanner. For minutia matching, an alignment-based elastic matching algorithm has been developed. This algorithm is capable of finding the correspondences between minutiae in the input image and the stored template without resorting to exhaustive search and has the ability of adaptively compensating for the nonlinear deformations and inexact pose transformations between fingerprints. The system has been tested on two sets of fingerprint images captured with inkless scanners. The verification accuracy is found to be acceptable. Typically, a complete fingerprint verification procedure takes, on an average, about eight seconds on a SPARC 20 workstation. These experimental results show that our system meets the response time requirements of online verification with high accuracy.
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paper_title: Image enhancement and minutiae matching in fingerprint verification

paper_content:

Fingerprint image enhancement and minutiae matching are two key steps in an automatic fingerprint identification system. In this paper, we develop a fingerprint image enhancement algorithm based on orientation fields; According to the principles of Jain et al.'s matching algorithm, we also introduce ideas along the following three aspects: introduction of ridge information into the minutiae matching process in a simple but effective way, which solves the problem of reference point pair selection with low computational cost; use of a variable sized bounding box to make our algorithm more robust to non-linear deformation between fingerprint images; use of a simpler alignment method in our algorithm. Experiments using the Fingerprint Verification Competition 2000 (FVC2000) databases with the FVC2000 performance evaluation show that these ideas are effective.
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paper_title: Fingerprint Image Enhancement: Algorithm and Performance Evaluation

paper_content:

In order to ensure that the performance of an automatic fingerprint identification/verification system will be robust with respect to the quality of input fingerprint images, it is essential to incorporate a fingerprint enhancement algorithm in the minutiae extraction module. We present a fast fingerprint enhancement algorithm, which can adaptively improve the clarity of ridge and valley structures of input fingerprint images based on the estimated local ridge orientation and frequency. We have evaluated the performance of the image enhancement algorithm using the goodness index of the extracted minutiae and the accuracy of an online fingerprint verification system. Experimental results show that incorporating the enhancement algorithm improves both the goodness index and the verification accuracy.
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paper_title: On the similarity of identical twin fingerprints

paper_content:

Reliable and accurate verification of people is extremely important in a number of business transactions as well as access to privileged information. Automatic verification methods based on physical biometric characteristics such as fingerprint or iris can provide positive verification with a very high accuracy. However, the biometrics-based methods assume that the physical characteristics of an individual (as captured by a sensor) used for verification are sufficiently unique to distinguish one person from another. Identical twins have the closest genetics-based relationship and, therefore, the maximum similarity between fingerprints is expected to be found among identical twins. We show that a state-of-the-art automatic fingerprint verification system can successfully distinguish identical twins though with a slightly lower accuracy than nontwins.
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paper_title: Detecting Faces in Images : A Survey

paper_content:

Images containing faces are essential to intelligent vision-based human-computer interaction, and research efforts in face processing include face recognition, face tracking, pose estimation and expression recognition. However, many reported methods assume that the faces in an image or an image sequence have been identified and localized. To build fully automated systems that analyze the information contained in face images, robust and efficient face detection algorithms are required. Given a single image, the goal of face detection is to identify all image regions which contain a face, regardless of its 3D position, orientation and lighting conditions. Such a problem is challenging because faces are non-rigid and have a high degree of variability in size, shape, color and texture. Numerous techniques have been developed to detect faces in a single image, and the purpose of this paper is to categorize and evaluate these algorithms. We also discuss relevant issues such as data collection, evaluation metrics and benchmarking. After analyzing these algorithms and identifying their limitations, we conclude with several promising directions for future research.
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Title: A Review of Performance Evaluation for Biometrics Systems

Section 1: Introduction
Description 1: Introduce the importance and relevance of biometric systems for personal authentication, and outline the focus of the paper on performance evaluation.

Section 2: Definition and Characteristics
Description 2: Discuss the basic definition of biometric systems, their characteristics, and the different types of biometric features used.

Section 3: Biometric Feature
Description 3: Explain how biometric systems use different parts of the body for authentication and the criteria for the selection of biometric features.

Section 4: Applications
Description 4: Outline the various applications of biometric features in different domains and contexts.

Section 5: System Architecture
Description 5: Describe the architecture of biometric systems, including input devices, authentication algorithms, databases, and the main processes involved.

Section 6: Evaluation Methodology
Description 6: Detail the stages of evaluation, including planning, performing, and analyzing, and discuss the different types of evaluation protocols.

Section 7: Planning Evaluation
Description 7: Explain the process of designing the test protocol, selecting subjects, and setting up the environment for evaluation.

Section 8: Performing Evaluation and Analyzing Results
Description 8: Describe the procedures for performing evaluations and analyzing the results using various measures and curves.

Section 9: Evaluation for System Modules
Description 9: Discuss the evaluation of different modules within a biometric system, including acquisition, feature extraction, and matching algorithms.

Section 10: Factor-based Evaluation
Description 10: Introduce the concept of factor-based evaluation considering genetic, social, environmental, and user factors affecting biometric systems.

Section 11: Environmental Factors
Description 11: Analyze the impact of environmental and user conditions on the performance of biometric systems.

Section 12: Related Works on Evaluation
Description 12: Provide an overview of various biometric evaluation projects and their methodologies.

Section 13: Fingerprint Recognition Systems
Description 13: Discuss fingerprint recognition systems in detail, including their components, processes, and performance evaluation methods.

Section 14: The State of the Art of Fingerprint Recognition
Description 14: Present current advancements and challenges in fingerprint recognition technologies and evaluation methods.

Section 15: Discussion
Description 15: Analyze the findings from the evaluation of biometric systems and identify areas for improvement and practical application.

Section 16: Conclusions
Description 16: Summarize the key points of the paper and suggest future research directions in the performance evaluation of biometric systems.
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