The generation and manipulation of digital images is made simple by widely available digital cameras and image processing software. As a consequence, we can no longer take the authenticity of a digital image for granted. This thesis investigates the problem of protecting the trustworthiness of digital images. Image authentication aims to verify the authenticity of a digital image. General solution of image authentication is based on digital signature or watermarking. A lot of studies have been conducted for image authentication, but thus far there has been no solution that could be robust enough to transmission errors during images transmission over lossy channels. On the other hand, digital image forensics is an emerging topic for passively assessing image authenticity, which works in the absence of any digital watermark or signature. This thesis focuses on how to assess the authenticity images when ...

Computer vision-based analysis of human facial video provides information regarding to expression, diseases symptoms, and physiological parameters such as heartbeat rate, blood pressure and respiratory rate. It also provides a convenient source of heartbeat signal to be used in biometrics and forensics. This thesis is a collection of works done in five themes in the realm of computer vision-based facial image analysis: Monitoring elderly patients at private homes, Face quality assessment, Measurement of physiological parameters, Contact-free heartbeat biometrics, and Decision support system for healthcare. The work related to monitoring elderly patients at private homes includes a detailed survey and review of the monitoring technologies relevant to older patients living at home by discussing previous reviews and relevant taxonomies, different scenarios for home monitoring solutions for older patients, sensing and data acquisition techniques, data processing and analysis techniques, available datasets for ...

The use of machine-learning for multimedia forensics is gaining more and more consensus, especially due to the amazing possibilities offered by modern machine learning techniques. By exploiting deep learning tools, new approaches have been proposed whose performance remarkably exceed those achieved by state-of-the-art methods based on standard machine-learning and model-based techniques. However, the inherent vulnerability and fragility of machine learning architectures pose new serious security threats, hindering the use of these tools in security-oriented applications, and, among them, multimedia forensics. The analysis of the security of machine learning-based techniques in the presence of an adversary attempting to impede the forensic analysis, and the development of new solutions capable to improve the security of such techniques is then of primary importance, and, recently, has marked the birth of a new discipline, named Adversarial Machine Learning. By focusing on Image Forensics and ...

The present doctoral thesis aims towards the development of new long-term, multi-channel, audio-visual processing techniques for the analysis of bioacoustics phenomena. The effort is focused on the study of the physiology of the gastrointestinal system, aiming at the support of medical research for the discovery of gastrointestinal motility patterns and the diagnosis of functional disorders. The term "processing" in this case is quite broad, incorporating the procedures of signal processing, content description, manipulation and analysis, that are applied to all the recorded bioacoustics signals, the auxiliary audio-visual surveillance information (for the monitoring of experiments and the subjects' status), and the extracted audio-video sequences describing the abdominal sound-field alterations. The thesis outline is as follows. The main objective of the thesis, which is the technological support of medical research, is presented in the first chapter. A quick problem definition is initially ...

The increasing need for personal authentication in many daily applications has made biometrics a fundamental research area. In particular, handwritten signatures have long been considered one of the most valuable biometric traits. Signatures are the most popular method for identity verification all over the world, and people are familiar with the use of signatures for identity verification purposes in their everyday life. In fact, signatures are widely used in several daily transactions, being recognized as a legal means of verifying an individual’s identity by financial and administrative institutions. In addition, signature verification has the advantage of being a non-invasive biometric technique. Two categories of signature verification systems can be distinguished taking into account the acquisition device, namely, offline systems, where only the static image of the signature is available, and online systems, where dynamic information acquired during the signing process, ...

Steganography is the science that involves communicating secret data in an appropriate multimedia carrier, e.g., image, audio and video files. It comes under the assumption that if the feature is visible, the point of attack is evident, thus the goal here is always to conceal the very existence of the embedded data. It does not replace cryptography but rather boosts the security using its obscurity features. Steganography has various useful applications. However, like any other science it can be used for ill intentions. It has been propelled to the forefront of current security techniques by the remarkable growth in computational power, the increase in security awareness, e.g., individuals, groups, agencies, government and through intellectual pursuit. Steganography’s ultimate objectives, which are undetectability, robustness, resistance to various image processing methods and compression, and capacity of the hidden data, are the main factors ...

Automatic speaker recognition is the use of a machine to identify an individual from a spoken sentence. Recently, this technology has been undergone an increasing use in applications such as access control, transaction authentication, law enforcement, forensics, and system customisation, among others. One of the central questions addressed by this field is what is it in the speech signal that conveys speaker identity. Traditionally, automatic speaker recognition systems have relied mostly on short-term features related to the spectrum of the voice. However, human speaker recognition relies on other sources of information; therefore, there is reason to believe that these sources can play also an important role in the automatic speaker recognition task, adding complementary knowledge to the traditional spectrum-based recognition systems and thus improving their accuracy. The main objective of this thesis is to add prosodic information to a traditional ...

Every day we share our personal information with digital systems which are constantly exposed to threats. Security-oriented disciplines of signal processing have then received increasing attention in the last decades: multimedia forensics, digital watermarking, biometrics, network intrusion detection, steganography and steganalysis are just a few examples. Even though each of these fields has its own peculiarities, they all have to deal with a common problem: the presence of adversaries aiming at making the system fail. It is the purpose of Adversarial Signal Processing to lay the basis of a general theory that takes into account the impact of an adversary on the design of effective signal processing tools. By focusing on the most prominent problem of Adversarial Signal Processing, namely binary detection or Hypothesis Testing, we contribute to the above mission with a general theoretical framework for the binary detection ...

eXtended Reality (XR) technology, also called Mixed Reality (MR), is in constant development and improvement in terms of hardware and software to offer relevant experiences to users. One of the advances in XR has been the introduction of real visual information in the virtual environment, offering a more natural interaction with the scene and a greater acceptance of technology. Another advance has been achieved with the representation of the scene through a video that covers the entire environment, called 360-degree or omnidirectional video. These videos are acquired by cameras with omnidirectional lenses that cover the 360-degrees of the scene and are generally viewed by users through a head-tracked Head Mounted Display (HMD). Users only visualize a subset of the 360-degree scene, called viewport, which changes with the variations of the viewing direction of the users, determined by the movements of ...

This Thesis is focused on the combination of multiple biometric traits for automatic person authentication, in what is called a multimodal biometric system. More generally, any type of biometric information can be combined in what is called a multibiometric system. The information sources in multibiometrics include not only multiple biometric traits but also multiple sensors, multiple biometric instances (e.g., different fingers in fingerprint verification), repeated instances, and multiple algorithms. Most of the approaches found in the literature for combining these various information sources are based on the combination of the matching scores provided by individual systems built on the different biometric evidences. The combination schemes following this architecture are typically based on combination rules or trained pattern classifiers, and most of them assume that the score level fusion function is fixed at verification time. This Thesis considers the problem of ...

Every day we share our personal information through digital systems which are constantly exposed to threats. For this reason, security-oriented disciplines of signal processing have received increasing attention in the last decades: multimedia forensics, digital watermarking, biometrics, network monitoring, steganography and steganalysis are just a few examples. Even though each of these elds has its own peculiarities, they all have to deal with a common problem: the presence of one or more adversaries aiming at making the system fail. Adversarial Signal Processing lays the basis of a general theory that takes into account the impact that the presence of an adversary has on the design of effective signal processing tools. By focusing on the application side of Adversarial Signal Processing, namely adversarial information fusion in distributed sensor networks, and adopting a game-theoretic approach, this thesis contributes to the above mission ...

This Thesis is focused on the quality assessment of biometric signals and its application to multimodal biometric systems. Since the establishment of biometrics as an specific research area in late 90s, the biometric community has focused its efforts in the development of accurate recognition algorithms and nowadays, biometric recognition is a mature technology that is used in many applications. However, we can notice recent studies that demonstrate how performance of biometric systems is heavily affected by the quality of biometric signals. Quality measurement has emerged in the biometric community as an important concern after the poor performance observed in biometric systems on certain pathological samples. We first summarize the state-of-the-art in the biometric quality problem. We present the factors influencing biometric quality, which mainly have to do with four issues: the individual itself, the sensor used in the acquisition, the ...

In this doctoral dissertation, we principally explore the use of the temporal information available in video sequences for person and gender recognition; in particular, we focus on the analysis of head and facial motion, and their potential application as biometric identifiers. We also investigate how to exploit as much video information as possible for the automatic recognition; more precisely, we examine the possibility of integrating the head and mouth motion information with facial appearance into a multimodal biometric system, and we study the extraction of novel spatio-temporal facial features for recognition. We initially present a person recognition system that exploits the unconstrained head motion information, extracted by tracking a few facial landmarks in the image plane. In particular, we detail how each video sequence is firstly pre-processed by semiautomatically detecting the face, and then automatically tracking the facial landmarks over ...

The problem of finding images, video clips and music, given time, place, interest and mood has kept an immense number of scientists and technology developers busy in the past twenty years. However, straightforward attempts to apply textbased search to non-textual data still seem to be the only viable solution. In spite of the numerous ideas proposed so far in the MIR (Multimedia Information Retrieval) research field, it is remarkable that hardly any significant success story, and in particular a commercially relevant one, has been reported. This thesis addresses the reasons that have prevented broad practical deployment of theories and algorithms for searching and retrieving content in multimedia data collections and proposes novel, generic and robust solutions. In particular, the thesis focuses on the problems that typically emerge when dealing with realistic use cases built around real-life systems, noisy data and ...

The proliferation of handheld devices such as smartphones and tablets brings a new scenario for biometric authentication, and in particular to automatic signature verification. Research on signature verification has been traditionally carried out using signatures acquired on digitizing tablets or Tablet-PCs. This PhD Thesis addresses the problem of user authentication on handled devices using handwritten signatures and graphical passwords based on free-form doodles, as well as the effects of biometric aging on signatures. The Thesis pretends to analyze: (i) which are the effects of mobile conditions on signature and doodle verification, (ii) which are the most distinctive features in mobile conditions, extracted from the pen or fingertip trajectory, (iii) how do different similarity computation (i.e. matching) algorithms behave with signatures and graphical passwords captured on mobile conditions, and (iv) what is the impact of aging on signature features and verification ...