Multimodal biometric contactless authentication using the artificial intelligence

Biometrické autentizační systémy slouží k ověření identity osoby pomocí jedinečných tělesných znaků (otisk prstu, geometrie obličeje, duhovka oka, sítnice oka, geometrie ruky, hlas atd.). Výhodou tohoto typu autentizace je, že si osoba nemusí pamatovat několikamístné heslo nebo s sebou neustále nosit snadno zcizitelný token (přihlašovací kartu). Biometrická autentizace je rychlou, pohodlnou a velice přesnou metodou. Mezi hlavní výhody biometrické autentizace patří vysoký stupeň spolehlivosti, nulové provozní náklady, rychlost, praktičnost a zřejmost. Oblast využití biometrických systémů můžeme rozdělit do dvou sfér a to do bezpečnostně-komerční (ochrana počítačů a dat, zajištění komfortu, vstup do objektů) a forenzní (soudní, kriminalistická a vyšetřovací). Podstatou všech biometrických systémů je automatizované snímání biometrických charakteristik a jejich následné porovnání s dříve získanými údaji. Jedním z cílů v oblasti bezpečnosti je vytvoření komplexních systémů založených na kombinaci měření více charakteristik. Z tohoto důvodu se tato práce zaměřuje na návrh biometrického autentizačního systému založeného na dvou charakteristikách a to na hlase a geometrii obličeje, kde hlavní roli v oblasti klasifikace bude hrát strojové učení. Vytvořením takového systému pracujícího na bázi vícenásobné autentizace s robustně navrženými klasifikátory vzniká unikátní nástroj pro bezdotykovou autentizaci, který může být v budoucnu využit jako přístupový systém v budovách či pro ověření přístupu osob k různým zařízením.Biometric authentication systems are used to verify the identity of the person using unique physical features (fingerprint, facial geometry, iris, retina, hand geometry, voice, etc.). The advantage of this type of authentication is that a person does not need to remember a password or always carry an easily stealable token (registration card). Biometric authentication is a fast, convenient and very precise method. Among the main benefits of biometric authentication include a high reliability, zero operating costs, speed, practicality, and clarity. The field of application of biometric systems can be divided into two spheres - security-commercial (security of computers and data, ensuring a comfort, entry into buildings) and forensic (judicial, forensic and investigative). The basic of all biometric systems is automated scanning of biometric characteristics and their subsequent comparison with previously collected data. One of the goal in the field of security is the realization of complex systems based on a combination of multiple characteristics measurements. For this reason, this work focuses on the design of a biometric authentication system based on two characteristics - voice and facial geometry, where the main role in the classification is played by machine learning. By creating such a multimodal autentication system with robustly designed classifiers, a unique contactless authentication tool is created, which can be used as an building access system or personal access system in the future.440 - Katedra telekomunikační technikyvyhově

Digital Signal Processing Using Opensource GNU OCTAVE

Import 26/06/2013Cílem této práce je poskytnout studentům předmětů zabývajících se zpracováním signálů alternativu výpočetního softwaru, který je volně dostupný na rozdíl například od licencovaného programu Matlab. K tomuto účelu je vytvořena pokročilá uživatelská příručka práce v programu Octave, ve které jsou probírány jednotlivé kapitoly týkající se zpracování signálů. V kapitolách jsou uvedena úskalí realizace v Octave a nejdůležitější změny oproti programu Matlab. K většině kapitol jsou vytvořeny programy s podrobným komentářem, ve kterých je prakticky ukázána problematika dané kapitoly.The aim of this thesis is to offer the students of the subjects dealing with signals processing an alternative of a computing software, that is free of charge compared to i.e. the programme Matlab. For this purpose it was evolved an advanced user manual of how to work in the background of the programme Octave, in which individual chapters about signals processing are being addressed. In the chapters, both, the issue of realization in the programme Octave and the most important changes compared to the programme Matlab, are stated. For most of the chapters programmes with detailed narratives were created, in which the problematics of each chapter is practically explained.440 - Katedra telekomunikační technikyvýborn

Human abnormal behavior impact on speaker verification systems

Human behavior plays a major role in improving human-machine communication. The performance must be affected by abnormal behavior as systems are trained using normal utterances. The abnormal behavior is often associated with a change in the human emotional state. Different emotional states cause physiological changes in the human body that affect the vocal tract. Fear, anger, or even happiness we recognize as a deviation from a normal behavior. The whole spectrum of human-machine application is susceptible to behavioral changes. Abnormal behavior is a major factor, especially for security applications such as verification systems. Face, fingerprint, iris, or speaker verification is a group of the most common approaches to biometric authentication today. This paper discusses human normal and abnormal behavior and its impact on the accuracy and effectiveness of automatic speaker verification (ASV). The support vector machines classifier inputs are Mel-frequency cepstral coefficients and their dynamic changes. For this purpose, the Berlin Database of Emotional Speech was used. Research has shown that abnormal behavior has a major impact on the accuracy of verification, where the equal error rate increase to 37 %. This paper also describes a new design and application of the ASV system that is much more immune to the rejection of a target user with abnormal behavior.Web of Science6401274012

Detection of physical impacts of shipping containers during handling operations using the impact detection methodology

The transportation of cargo inside shipping containers is a risky operation that requires constant monitoring activities and real-time operational actions. Yet, the detection of the real dynamics of the container and the surrounding infrastructure and extraction of true subsequent critical events is still an unresolved issue among engineers. In this paper, we analyze the new physical impact detection method, namely the Impact Detection Methodology (IDM), to detect the most obvious and force-dependent impacts from acceleration data, using the IoT sensor in an experimental environment using the heavy machinery of a seaport. By variating the threshold level, we have observed the changes in the number of impacts detected within three separate case studies. Results suggest that the optimal parameters tend to provide an adequate number of events, yet even the slightest change in the threshold level can increase or decrease the number of detected impacts in a non-linear fashion, making the detection harder, due to unforeseen external impacts on the dataset, the filtering of which is still the main priority of our future research.Web of Science109art. no. 125

Low frequency analog amplifiers design

Import 04/07/2011V první části mé práce se zabývám přehledem základních principů nízkofrekvenčních zesilovačů, jako jsou základní parametry (napěťové zesílení, proudové zesílení, výkonové zesílení, vstupní impedance, výstupní impedance a dynamický rozsah), základní zapojení (SE, SC a SB), pracovní třídy (A, B, AB a D), rozdělení zesilovačů na napěťové a výkonové, druhy vazeb (přímá, kapacitní a induktivní), druhy zátěže (odporová a induktivní) a metody řízení pracovního budu (kompresor dynamiky a koncové zesilovače se samočinným nastavením pracovního bodu v závislosti na buzení). V druhé části jsem navrhl zesilovač s kompresorem dynamiky a pomocí RC stavebnice, nepájivého pole a programu Multisim 9 jsem ověřil jeho funkčnost a proměřil jeho vlastnosti. Proměřil jsem závislost výstupního napětí na vstupním a z naměřených hodnot jsem vypočetl dynamický rozsah. V poslední části jsem navrhl zesilovač pracující ve třídě A, u kterého jsem proměřil a vypočetl stejné parametry jako u kompresoru dynamiky. Na závěr jsem naměřené parametry obou zesilovačů porovnal.The first section of the dissertation gives an overview of principles of audio amplifiers, such as basic parameters (voltage gain, current gain, power gain, input impedance, output impedance, and dynamic range), basic integration (SE, SC, and SB), amplifier classes (A, B, AB and D), division of amplifiers into voltage and power amplifiers, types of couplings (direct, capacitive, and inductive), types of loads (resistive and inductive), and methods of operating point control (dynamics compressor and output amplifiers with self-alignment of an operating point depending upon excitation). In the second part, an amplifier with a dynamics compressor was designed; its functionality was verified with aid of RC construction, breadboard and Multisim 9 programme, and its features were measured. The dependence of output voltage on input voltage was measured and the measurement was used to calculate the dynamic range. The last section proposes an amplifier operating in the A class; same parameters as for dynamics compressor were measured and calculated. Then, measured parameters of both amplifiers were compared.440 - Katedra telekomunikační technikyvelmi dobř

Detection of speaker liveness with CNN isolated word ASR for verification systems

The article proposes a new speaker liveness test for speech verification systems. Biometric authentication systems based on speaker verification are often subject to presentation attacks which use the target speaker's recorded speech. We propose a liveness test which uses CNN isolated word ASR as a countermeasure to repel attacks during the verification process. The liveness test incorporates the extraction of MFCC coefficients and the CNN classifier. Reliability of the recognition of isolated words is verified against a validation dataset of various sizes. The achieved results verified the system's reliability, which decreased slightly as the size of the keyword dataset increased. The proposed method represents a simple and effective security component against presentation attacks for existing SV systems.Web of Scienc

Deep learning serves voice cloning: How vulnerable are automatic speaker verification systems to spoofing trials?

This article verifies the reliability of automatic speaker verification (ASV) systems on new synthesis methods based on deep neural networks. ASV systems are widely used and applied regarding secure and effective biometric authentication. On the other hand, the rapid deployment of ASV systems contributes to the increased attention of attackers with newer and more sophisticated spoofing methods. Until recently, speech synthesis of the reference speaker did not seriously compromise the latest ASV systems. This situation is changing with the deployment of deep neural networks into the synthesis process. Projects including WaveNet, Deep Voice, Voice Loop, and many others generate very natural and high-quality speech that may clone voice identity. We are slowly approaching an era where we will not be able to recognize a genuine voice from a synthesized one. Therefore, it is necessary to define the robustness of current ASV systems to new methods of voice cloning. In this article, well-known SVM and GMM as well as new CNN-based ASVs are applied and subjected to synthesized speech from Tacotron 2 with the WaveNet TTS system. The results of this work confirm our concerns regarding the reliability of ASV systems against synthesized speech.Web of Science58210510

Detecting shipping container impacts with vertical cell guides inside container ships during handling operations

Due to the mechanical nature of container handling operations, as well as natural factors, container and handling infrastructure suffers various types of damage during use, especially within the tight and enclosed environments of a ship's hull. In this operational environment, it is critical to detect any sort of physical impacts between the vertical cell guides of the ship's hull and the container. Currently, an inspection of impacts and evaluation of any consequences is performed manually, via visual inspection processes. This process is time-consuming and relies on the technical expertise of the personnel involved. In this paper, we propose a five-step impact-detection methodology (IDM), intended to detect only the most significant impact events based on acceleration data. We conducted real measurements in a container terminal using a sensory device placed on the spreader of the quay crane. The proposed solution identified an average of 12.8 container impacts with the vertical cell guides during common handling operations. In addition, the results indicate that the presented IDM can be used to recognize repeated impacts in the same space of each bay of the ship, and can be used as a decision support tool for predictive maintenance systems.Web of Science227art. no. 275