Martin Drahansky

Erratum to “New Optical Methods for Liveness Detection on Fingers”

This paper is devoted to new optical methods, which are supposed to be used for liveness detection on fingers. First we describe the basics about fake finger use in fingerprint recognition process and the possibilities of liveness detection. Then we continue with introducing three new liveness detection methods, which we developed and tested in the scope of our research activities--the first one is based on measurement of the pulse, the second one on variations of optical characteristics caused by pressure change, and the last one is based on reaction of skin to illumination with different wavelengths. The last part deals with the influence of skin diseases on fingerprint recognition, especially on liveness detection.

Real-time Terrain Deformations

This paper presents a method for a physically based real-time terrain deformation. The motivation originates from the fact that there exist many deformable models, but the terrain deformation is a special problem in the field of computer graphics. OpenSceneGraph toolkit provides an excellent environment for the large terrain visualization and it was accepted as a standard for many graphic specialists. Therefore, the main goal of this method is the local deformation ability of some large terrain, which is represented by a sub-graph of OpenSceneGraph scene. However, the technique may be easily adaptable to any terrain representation. The results show a great potential of the used method and thus there is outlined the future work at the end.

Liveness Detection based on Fine Movements of the Fingertip Surface

We propose a novel method for fingerprint liveness detection, which is based on the analysis of fine movements of the fingertip surface, which are induced by volume changes due to the blood flow. Our method can be implemented in combination with standard optical fingerprint scanners. We present some background information on fingerprint liveness detection such as already proposed methods for liveness detection based on skin temperature and skin resistance. Two different possible implementations of our new method are sketched and initial experiences with our test setup are presented. We also outline how we proceeded to further investigate the feasibility of the proposed method

Facial biometrics for situational awareness systems

This study contributes to developing the concept of decision-making support in biometric-based situational awareness systems. Such systems assist users in gathering and analysing biometric data, and support the decision-making on the human behavioural pattern and/or authentication. As an example, the authors consider a facial biometric assistant that functions based on multi-spectral biometrics in visible and infrared bands; it involves facial expression recognition, face recognition in both spectra, as well as estimation of physiological parameters. The authors also investigate usage of facial biometrics for the semantic representation for advanced decision-making.

Liveness Detection in Biometrics

The biometric systems, oriented in this chapter especially on fingerprints, have been introduced in the previous chapters. The functionality of such systems is influenced not only by the used technology, but also by the surrounding environment (including skin or other diseases). Biased or damaged biometric samples could be rejected after revealing their poor quality, or may be enhanced, what leads to the situation that samples, which would be normally rejected, are accepted after the enhancement process. But this process could present also a risk, because the poor quality of a sample could be caused not only by the sensor technology or the environment, but also by using an artificial biometric attribute (imitation of a finger(print)). Such risk is not limited just to the deceptional technique, but if we are not able to recognize whether an acquired biometric sample originates from a genuine living user or an impostor, we would then scan an artificial fake and try to enhance its quality using an enhancement algorithm. After a successful completion of such enhancement, such fake fingerprint would be compared with a template and if a match is found, the user is accepted, notwithstanding the fact that he can be an impostor! Therefore the need of careful liveness detection, i.e. the recognition whether an acquired biometric sample comes from a genuine living user or not, is crucial.

Biometric-Enabled Authentication Machines: A Survey of Open-Set Real-World Applications

This paper revisits the concept of an authentication machine (A-machine) that aims at identifying/verifying humans. Although A-machines in the closed-set application scenario are well understood and commonly used for access control utilizing human biometrics (face, iris, and fingerprints), open-set applications of A-machines have yet to be equally characterized. This paper presents an analysis and taxonomy of A-machines, trends, and challenges of open-set real-world applications. This paper makes the following contributions to the area of open-set A-machines: 1) a survey of applications; 2) new novel life cycle metrics for theoretical, predicted, and operational performance evaluation; 3) a new concept of evidence accumulation for risk assessment; 4) new criteria for the comparison of A-machines based on the notion of a supporting assistant; and 5) a new approach to border personnel training based on the A-machine training mode. It offers a technique for modeling A-machines using belief (Bayesian) networks and provides an example of this technique for biometric-based e-profiling.

Influence of Skin Diseases on Fingerprint Recognition

There are many people who suffer from some of the skin diseases. These diseases have a strong influence on the process of fingerprint recognition. People with fingerprint diseases are unable to use fingerprint scanners, which is discriminating for them, since they are not allowed to use their fingerprints for the authentication purposes. First in this paper the various diseases, which might influence functionality of the fingerprint-based systems, are introduced, mainly from the medical point of view. This overview is followed by some examples of diseased finger fingerprints, acquired both from dactyloscopic card and electronic sensors. At the end of this paper the proposed fingerprint image enhancement algorithm is described.

Experiments with Skin Resistance and Temperature for Liveness Detection

This article deals with liveness detection for biometric security systems which are based on fingerprint recognition. The article gives a global overview of known methods. At the end there are stated two experiments made with skin resistance and temperature. Based on our results, it was proven that these two skin characteristics are probably not suitable for liveness detection using this approach.

Inspired by Bertillon - Recognition based on anatomical features from 3D face scans

We present an automatic 3D face recognition algorithm that is inspired by Alphonse Bertillons anthropometry. Our recognition pipeline consists of several steps. First, the facial landmarks such as the tip of the nose or the inner eye corners are detected. Subsequently the head rotation is compensated during the orientation normalization process. The facial features are extracted by performing 61 different measures. We also present a feature evaluation function that rates individual components of the feature vector. Finally, our results are compared with two other 3D face recognition methods. We show that the multi-algorithmic system consisting of the anatomical-based recognition together with the eigenfaces method and the recognition using histogram-based features reaches significantly better results than any of the employed methods individually.

New optical methods for liveness detection on fingers.

This paper is devoted to new optical methods, which are supposed to be used for liveness detection on fingers. First we describe the basics about fake finger use in fingerprint recognition process and the possibilities of liveness detection. Then we continue with introducing three new liveness detection methods, which we developed and tested in the scope of our research activities—the first one is based on measurement of the pulse, the second one on variations of optical characteristics caused by pressure change, and the last one is based on reaction of skin to illumination with different wavelengths. The last part deals with the influence of skin diseases on fingerprint recognition, especially on liveness detection.