Existing invisible object tagging methods are prone to low resolution, which impedes tracking performance. We present BrightMarker, a fabrication method that uses fluorescent filaments to embed easily trackable markers in 3D printed color objects. By using an infrared-fluorescent filament that "shifts" the wavelength of the incident light, our optical detection setup filters out all the noise to only have the markers present in the infrared camera image. The high contrast of the markers allows us to track them robustly regardless of the moving objects’ surface color.

The design and implementation of effective and efficient biometric systems presents a series of challenges to information technology (IT) designers to ensure robust performance. One of the most important factors across biometric systems, aside from algorithmic matching ability, is the human interaction influence on performance. Changes in biometric system paradigms have motivated further testing methods, especially within mobile environments, where the interaction with the device has fewer environmental constraints, which may severely affect system performance. Testing methods involve the need for reflecting on the influence of user-system interaction on the overall system performance in order to provide information for design and testing. This paper reflects on the state of the art of biometric systems interaction assessment, leading to a comprehensive document of the relevant research and standards in this area. Furthermore, the current challenges are discussed and thus we provide a roadmap for the future of biometrics systems interaction research.

The Mobile Pass project focused its efforts on developing a technologically advanced mobile equipment for land border crossing points. During the project execution, a mobile device supporting biometric recognition (face and fingerprint) and passport checking was designed and developed. To test this new equipment under an operational environment, a usability evaluation was carried out in the Sculeni border control (border of Romania with Moldavia), being the operators Romanian Policemen and the data subjects' real volunteer travelers. The equipment was used for 2 days under different conditions in real scenarios, and the usability evaluation carried out follows the ISO 9241-11:1998 standard. A total of 93 participants completed the new border checking and fulfilled a satisfaction survey at the end of the experiment. This paper describes the evaluation and reports some preliminary results on the user-Automatic Border Control system interaction and the final conclusions obtained at the end of the project, resulting in a valuable guide for designing user interaction in security areas.

The use of biometrics keeps growing. Every day, we use biometric recognition to unlock our phones or to have access to places such as the gym or the office, so we rely on the security manufacturers offer when protecting our privileges and private life. It is well known that it is possible to hack into a fingerprint sensor using fake fingers made of Play‐Doh and other easy‐to‐obtain materials but to what extent? Is this true for all users or only for specialists with a deep knowledge on biometrics? Are smartphone fingerprint sensors as reliable as desktop sensors? To answer these questions, we performed 3 separate evaluations. First, we evaluated 4 desktop fingerprint sensors of different technologies by attacking them with 7 different fake finger materials. All of them were successfully attacked by an experienced attacker. Secondly, we carried out a similar test on 5 smartphones with embedded sensors using the most successful materials, which also hacked the 5 sensors. Lastly, we gathered 15 simulated attackers with no background in biometrics to create fake fingers of several materials, and they had one week to attack the fingerprint sensors of the same 5 smartphones, with the starting point of a short video with the techniques to create them. All 5 smartphones were successfully attacked by an inexperienced attacker. This paper will provide the results achieved, as well as an analysis on the attack potential of every case. All results are given following the metrics of the standard ISO/IEC 30107‐3.

Biometric recognition provides means to guarantee security in a wide range of services. Unfortunately, their usability is limited and they are not convenient for people with accessibility issues. To prevent the rejection of the technology, those systems should be improved by using a user-centric-design approach and by applying current accessibility standards. This work describes the design, development and evaluation of a mobile app for making payments in Points of Sale (PoS) using biometric recognition. The system has been tested by elderly persons. Our findings show accessibility issues and the most critical requirements to be covered. This is one of the first researches based on the European standard EN 301 549.

This paper presents the implementation of a speaker-verification system on field programmable gate array. The algorithm is executed by software over an embedded system that includes a MicroBlaze microprocessor connected to a vector floating-point unit (VFPU). The VFPU is designed to speed up the resolution of any vector floating-point operation involved in the verification algorithm, whereas the microprocessor manages the control of the process and executes the rest of operations. With a clock frequency of 40 MHz, the system is capable of executing the complete algorithm in real time, processing a voice frame in 9.1 ms. The same verification process was carried out for two different systems: 1) an ARM Cortex A8 microprocessor; and 2) configuring MicroBlaze with the scalar floating-point unit provided by Xilinx. The experimental results show that when comparing our proposed system against both systems, the number of clock cycles is reduced by a factor of 11.2× and 15.4×, respectively. The main advantage of the VFPU is its flexibility, which allows quick adaptation of the software to the potential changes produced in both the system and the user requirements. The algorithm was tested over a public database that contains the utterances of different users acquired under different environmental conditions, providing good recognition rates.

Actual trends in HCI tend to move systems to mobile environments. Moreover, biometrics is a technology that is entering maturity, getting involved in several security architectures nowadays. Thus, migrating biometrics to mobile scenarios is a trending topic in the research community. Nevertheless, in this kind of systems, usability has been put aside in the intent of produce better performance and it could involve undesirable results. In this work a behavioural biometric modality (handwritten signature recognition) is tested in mobile environments, in order to obtain a complete usability evaluation. Users signed in an iPad with different styluses in different scenarios, correlating performance results with several usability parameters (gathered through video, notes and forms) and obtaining interesting outcomes.

In many applications user authentication has to be carried out by portable devices. Usually these devices are personal tokens carried by users, which have many constraints regarding their computational performance, occupied area, and power consumption. These kinds of devices must deal with such constraints, while also maintaining high performance rates in the authentication process. This paper provides solutions to designing such personal tokens where biometric authentication is required. In this paper, iris biometrics have been chosen to be implemented due to the low error rates and the robustness their algorithms provide. Several design alternatives are presented, and their analyses are reported. With these results, most of the needs required for the development of an innovative identification product are covered. Results indicate that the architectures proposed herein are faster (up to 20 times), and are capable of obtaining error rates equivalent to those based on computer solutions. Simultaneously, the security and cost for large quantities are also improved.

Biometrics is a new technology that provides a secure identification, which is being used more and more these days. However, sensors and biometric systems are usually only tested by their own suppliers, and rarely an independent evaluation of these products is carried out. Also, when evaluating a biometric system/device, many factors that can affect its performance, are not even considered. This is the case of the environmental conditions, i.e. humidity, temperature, etc. In this paper, authors propose an evaluation methodology for measuring environmental factors influence in biometric products and their applications. This methodology describes factors, tools, requirements and procedures, needed to perform this kind of performance evaluations.

We present here a report on a new Performance Evaluation System for Biometric Systems, which is secure, automatic and remote. This system will provide developers in Biometrics to progress in their works, avoiding problems with data protection policies related to testing, but without compromising the privacy of testing subjects. Biometric testing needs personal data to be recorded and used. Therefore in order to test their prototypes, researchers have to waste a lot of time and money for buying or creating testing databases. The solution described here offers the developers a secure and remote system which is available at all times, and which concentrates all private data in a secured centralized server. Also, as current standards, including standard APIs, are used, efforts needed by developers to use the system will be minimized, lowering also the overhead costs for testing purposes. The system is described by block diagrams as well as flowcharts.

Biometrics is nowadays one of the most promising techniques in authentication. Biometrics intends to identify a user by his/her physical and/or behavioural characteristic. Among all Biometric techniques, Iris recognition stands out, as its error rates are one of the lowest. The authors propose in this paper a hardware implementation based on FPGA for an iris biometric processor. By this solution a reduction of the processing time is obtained and security levels of the whole system are increased due to the reduction of software involved

Gaussian mixture modelling (GMM) is a statistical pattern recognition technique usually applied to speaker identification. This technique can be used with morphological features extracted from images. Therefore, this technique is applied to hand geometry biometrics in order to improve the results obtained with other verification techniques. This biometric technique, which is considered to be a low-medium security one, can be applied to high security environments due to its error rates below 5%. The features to enter the GMM algorithm can be extracted from a color image of the hand (both the top and the side view of it). This image can then be processed and its edge detected before a morphological analysis is performed, thus obtaining a feature vector as small as 12 bytes. In this paper, after a short introduction and a general overview of the GMMs, the whole process is explained.

A work in defining and implementing a biometric system based on hand geometry identification is presented here. Hand features are extracted from a color photograph taken when the user has placed his hand on a platform designed for such a task. Different pattern recognition techniques have been tested to be used in classification and/or verification from Euclidean distance to neural networks. Experimental results, up to a 97 percent rate of success in classification, will show the possibility of using this system in medium/high security environments with full acceptance from all users.