Adams Wai-Kin Kong

Competitive coding scheme for palmprint verification

There is increasing interest in the development of reliable, rapid and non-intrusive security control systems. Among the many approaches, biometrics such as palmprints provide highly effective automatic mechanisms for use in personal identification. This paper presents a new method for extracting features from palmprints using the competitive coding scheme and angular matching. The competitive coding scheme uses multiple 2-D Gabor filters to extract orientation information from palm lines. This information is then stored in a feature vector called the competitive code. The angular matching with an effective implementation is then defined for comparing the proposed codes, which can make over 9,000 comparisons within 1s. In our testing database of 7,752 palmprint samples from 386 palms, we can achieve a high genuine acceptance rate of 98.4% and a low false acceptance rate of 3/spl times/10/sup -6/%. The execution time for the whole process of verification, including preprocessing, feature extraction and final matching, is 1s.

Palmprint identification using feature-level fusion

In this paper, we propose a feature-level fusion approach for improving the efficiency of palmprint identification. Multiple elliptical Gabor filters with different orientations are employed to extract the phase information on a palmprint image, which is then merged according to a fusion rule to produce a single feature called the Fusion Code. The similarity of two Fusion Codes is measured by their normalized hamming distance. A dynamic threshold is used for the final decisions. A database containing 9599 palmprint images from 488 different palms is used to validate the performance of the proposed method. Comparing our previous non-fusion approach and the proposed method, improvement in verification and identification are ensured.

A study of identical twins' palmprints for personal verification

Automatic biometric systems based on human characteristics for personal identification have attracted great attention. Their performance highly depends on the distinctive information in the biometrics. Identical twins having the closest genetics-based relationship are expected to have maximum similarity in their biometrics. Classifying identical twins is a challenging problem for some automatic biometric systems. Palmprint has been studied for personal identification for over seven years. Most of the previous research concentrates on algorithm development. In this paper, we systemically examine palmprints from the same DNA for automatic personal identification and to uncover the genetically related palmprint features. The experimental results show that the three principal lines and some portions of weak lines are genetically related features but our palms still contain rich genetically unrelated features for classifying identical twins.

Feature-Level Fusion for Effective Palmprint Authentication

A feature-level fusion approach is proposed for improving the efficiency of palmprint identification. Multiple Gabor filters are employed to extract the phase information on a palmprint image, which is then merged according to a fusion rule to produce a single feature called the Fusion Code. The similarity of two Fusion Codes is measured by their normalized hamming distance. A database containing 7,752 palmprint images from 386 different palms is used to validate the performance of the proposed method. Empirically comparing our previous non-fusion approach and the proposed method, improvement in verification is ensured

An Analysis of IrisCode

IrisCode is an iris recognition algorithm developed in 1993 and continuously improved by Daugman. It has been extensively applied in commercial iris recognition systems. IrisCode representing an iris based on coarse phase has a number of properties including rapid matching, binomial impostor distribution and a predictable false acceptance rate. Because of its successful applications and these properties, many similar coding methods have been developed for iris and palmprint identification. However, we lack a detailed analysis of IrisCode. The aim of this paper is to provide such an analysis as a way of better understanding IrisCode, extending the coarse phase representation to a precise phase representation, and uncovering the relationship between IrisCode and other coding methods. Our analysis demonstrates that IrisCode is a clustering algorithm with four prototypes; the locus of a Gabor function is a 2-D ellipse with respect to a phase parameter and can be approximated by a circle in many cases; Gabor function can be considered as a phase-steerable filter and the bitwise hamming distance can be regarded as a bitwise phase distance. We also discuss the theoretical foundation of the impostor binomial distribution. We use this analysis to develop a precise phase representation which can enhance accuracy. Finally, we relate IrisCode and other coding methods.

Three measures for secure palmprint identification

Most previous research in the area of personal authentication using the palmprint as a biometric trait has concentrated on enhancing accuracy yet resistance to attacks is also a centrally important feature of any biometric security system. In this paper, we address three relevant security issues: template re-issuances, also called cancellable biometrics, replay attacks, and database attacks. We propose to use a random orientation filter bank (ROFB) as a feature extractor to generate noise-like feature codes, called Competitive Codes for templates re-issuances. Secret messages are hidden in templates to prevent replay and database attacks. This technique can be regarded as template watermarking. A series of analyses is provided to evaluate the security levels of the measures.

Analysis of Brute-Force Break-Ins of a Palmprint Authentication System

Biometric authentication systems are widely applied because they offer inherent advantages over classical knowledge-based and token-based personal-identification approaches. This has led to the development of products using palmprints as biometric traits and their use in several real applications. However, as biometric systems are vulnerable to replay, database, and brute-force attacks, such potential attacks must be analyzed before biometric systems are massively deployed in security systems. This correspondence proposes a projected multinomial distribution for studying the probability of successfully using brute-force attacks to break into a palmprint system. To validate the proposed model, we have conducted a simulation. Its results demonstrate that the proposed model can accurately estimate the probability. The proposed model indicates that it is computationally infeasible to break into the palmprint system using brute-force attacks

An evaluation of Gabor orientation as a feature for face recognition

Identifying a reliable feature is extremely important for all pattern recognition systems. The Gabor filter, which simultaneously captures spatial and frequency information, has been a vital component in numerous systems as a feature extractor. This filter produces three basic features - magnitude, phase, and orientation. Most face recognition methods based on Gabor filters use either the magnitude feature alone or a combination of the phase and magnitude features; very few are purely based on the phase feature, and the orientation feature is ignored. The aim of this paper is to evaluate these three basic features for face recognition using the FERET and AR face databases. The results show that the orientation feature is the most robust and distinctive feature, 20% and over 10% more accurate than the phase and magnitude features, respectively.

An analysis on accuracy of cancelable biometrics based on biohashing

Cancelable biometrics has been proposed for canceling and re-issuing biometric templates and for protecting privacy in biometrics systems. Recently, new cancelable biometric approaches are proposed based on BioHashing, which are random transformed feature-based cancelable biometrics. In this paper, we consider the accuracy of one of the cancelable biometrics based on BioHashing and face. Through this analysis, as an illustration, we would like to raise an issue to be considered in cancelable biometrics: accuracy may be traded for biometrics being cancelable.

Matching vein patterns from color images for forensic investigation

Child sexual abuse is a serious global problem and has gained public attention in recent years. Due to the popularity of digital cameras, many perpetrators take images of their sexual activities with child victims. Traditionally, it was difficult to use cutaneous vascular patterns for forensic identification, because they were nearly invisible in color images. Recently, this limitation was overcome using a computational method based on an optical model to uncover vein patterns from color images for forensic verification. This optical-based vein uncovering (OBVU) method is sensitive to the power of the illuminant and does not utilize skin color in images to obtain training parameters to optimize the vein uncovering performance. Prior publications have not included an automatic vein matching algorithm for forensic identification. As a result, the OBVU method only supported manual verification. In this paper, we propose two new schemes to overcome limitations in the OBVU method. Specifically, a color optimization scheme is used to derive the range of biophysical parameters to obtain training parameters and an automatic intensity adjustment scheme is used to enhance the robustness of the vein uncovering algorithm. We also developed an automatic matching algorithm for vein identification. This algorithm can handle rigid and non-rigid deformations and has an explicit pruning function to remove outliers in vein patterns. The proposed algorithms were examined on a database with 300 pairs of color and near infrared (NIR) images collected from the forearms of 150 subjects. The experimental results are encouraging and indicate that the proposed vein uncovering algorithm performs better than the OBVU method and that the uncovered patterns can potentially be used for automatic criminal and victim identification.