Computed tomography (CT) is a technique that uses computation to form an image of the inside of an object or person, by combining projections of that object or person. The word tomography is derived from the Greek word tomos, meaning slice. The basis for computed tomography was laid in 1917 by Johann Radon, an Austrian mathematician. Computed tomography has a broad range of applications, the best known being medical imaging (the CT scanner), where X-rays are used for making the projection images. The rst practical application of CT was, however, in astronomy, by Ronald Bracewell in 1956. He used CT to improve the resolution of radio-astronomical observations. The practical applications in this thesis are from electron tomography, where the images are made with an electron microscope, and from preclinical research, where the images are made with a CT scanner. There ...

This thesis introduces the rank-order model and investigates its use in several image restoration problems. More commonly used as filters, the rank-order operators are here employed as predictors. A Laplacian excitation sequence is chosen to complete the model. Images are generated with the model and compared with those formed with an AR model. A multidimensional rankorder model is formed from vector medians for use with multidimensional image data. The first application using the rank-order model is an impulsive noise detector. This exploits the notion of ‘multimodality’ in the histogram of a difference image of the degraded image and a rank-order filtered version. It uses the EM algorithm and a mixture model to automatically determine thresholds for detecting the impulsive noise. This method compares well with other detection methods, which require manual setting of thresholds, and to stack filtering, which requires ...

In biological research images are extensively used to monitor growth, dynamics and changes in biological specimen, such as cells or plants. Many of these images are used solely for observation or are manually annotated by an expert. In this dissertation we discuss several methods to automate the annotating and analysis of bio-images. Two large clusters of methods have been investigated and developed. A first set of methods focuses on the automatic delineation of relevant objects in bio-images, such as individual cells in microscopic images. Since these methods should be useful for many different applications, e.g. to detect and delineate different objects (cells, plants, leafs, ...) in different types of images (different types of microscopes, regular colour photographs, ...), the methods should be easy to adjust. Therefore we developed a methodology relying on probability theory, where all required parameters can easily ...

In the modern world, we are increasingly surrounded by computation devices with communication links and one or more microphones. Such devices are, for example, smartphones, tablets, laptops or hearing aids. These devices can work together as nodes in an acoustic sensor network (ASN). Such networks are a growing platform that opens the possibility for many practical applications. ASN based speech enhancement, source localization, and event detection can be applied for teleconferencing, camera control, automation, or assisted living. For this kind of applications, the awareness of auditory objects and their spatial positioning are key properties. In order to provide these two kinds of information, novel methods have been developed in this thesis. Information on the type of auditory objects is provided by a novel real-time sound classification method. Information on the position of human speakers is provided by a novel localization ...

Digital holography plays a crucial role in recent three dimensional imaging as well as microscopic applications. As a result, huge amounts of storage capacity will be involved for this kind of data. Therefore, it becomes necessary to develop efficient hologram compression schemes for storage and transmission purposes, which is the aim of this thesis. Particularly, the objective is the compression of digital holographic data obtained from phase-shifting interferometry. Unlike conventional approaches which encode certain representation of phase-shifting holographic data independently, the proposed work first studies the possible representations of phase-shifting holographic data and analyzes the redundancies in each representation. A new representation, referred to as shifted distance information, is selected as the compression target. Then, a vector lifting schemes based compression method is proposed to jointly encode this data. We also show the benefits that can be drawn from improving ...

Monitoring of vital signs is a key tool in medical diagnostics to asses the onset and the evolution of several diseases. Among fundamental vital parameters, such as the hearth rate, blood pressure and body temperature, the Respiratory Rate (RR) plays an important role. For this reason, respiration needs to be carefully monitored in order to detect potential signs or events indicating possible changes of health conditions. Monitoring of the respiration is generally carried out in hospital and clinical environments by the use of expensive devices with several sensors connected to the patient's body. A new research trend, in order to reduce healthcare service costs and make monitoring of vital signs more comfortable, is the development of low-cost systems which may allow remote and contactless monitoring; in such a context, an appealing method is to rely on video processing-based solutions. In ...

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 ...

Ground Penetrating Radar (GPR) is seen as one of several promising technologies aimed to help mine detection. GPR is sensitive to any inhomogeneity in the ground. Therefore any APM regardless of the metal content can be detected. On the other hand, all the inhomogeneities, which do not represent mines, show up as a clutter in GPR images. Moreover, it is known that reflectivity of APM is often weaker than that of stones, pieces of shrapnel and barbed wire, etc. Altogether these factors cause GPR to produce unacceptably high false alarm rate whilst it reaches the 99.6% detection rate which is prescribed by an UN resolution as a standard for humanitarian demining. The main goal of the work presented in the thesis is reduction of the false alarm rate while keeping the 99.6% detection rate intact. To reach this goal a ...

Fingerprint, is considered one of the most crucial scientific tools in solving criminal cases. This biometric feature is composed of unique and distinctive patterns found on the fingertips of each individual. With advancing technology and progress in forensic sciences, fingerprint analysis plays a vital role in forensic investigations and the analysis of evidence at crime scenes. The fingerprint patterns of each individual start to develop in early stagesof life and never change thereafter. This fact makes fingerprints an exceptional means of identification. In criminal cases, fingerprint analysis is used to decipher traces, evidence, and clues at crime scenes. These analyses not only provide insights into how a crime was committed but also assist in identifying the culprits or individuals involved. Computer-based fingerprint identification systems yield faster and more accurate results compared to traditional methods, making fingerprint comparisons in large databases ...

Our main purpose in this PhD thesis is to perform local frequential (or directional) processing in different kind of data (volumes, images or signals). To this end, filter banks (FBs) are studied. More precisely, we first investigate the existence and the construction of synthesis FBs inverse to a given FIR complex analysis FB. Through the study of the polyphase analysis matrix, we are able to propose methods to test the invertibility and to build one inverse FB. Using this inverse, we provide a parametrization of the set of synthesis FB, with which we optimize filter responses with different criteria. The same study is performed in the multidimensional case. Since FBs provide an efficient representation of structured information in data, it is then possible to preserve them while rejecting unwanted perturbations. By associating Stein’s principle and those FBs, we proposed two ...

The subject of this PhD thesis is the efficient and robust processing and analysis of the audio recordings that are derived from a call center. The thesis is comprised of two parts. The first part is dedicated to dialogue/non-dialogue detection and to speaker segmentation. The systems that are developed are prerequisite for detecting (i) the audio segments that actually contain a dialogue between the system and the call center customer and (ii) the change points between the system and the customer. This way the volume of the audio recordings that need to be processed is significantly reduced, while the system is automated. To detect the presence of a dialogue several systems are developed. This is the first effort found in the international literature that the audio channel is exclusively exploited. Also, it is the first time that the speaker utterance ...

This dissertation is concerned with the application of the theory of rational functions in signal processing. The PhD thesis summarizes the corresponding results of the author’s research. Since the systems of rational functions are defined by the collection of inverse poles with multiplicities, the following parameters should be determined: the number, the positions and the multiplicities of the inverse poles. Therefore, we develop the hyperbolic variant of the so-called Nelder–Mead and the particle swarm optimization algorithm. In addition, the latter one is integrated into a more general multi-dimensional framework. Furthermore, we perform a detailed stability and error analysis of these methods. We propose an electrocardiogram signal generator based on spline interpolation. It turns to be an efficient tool for testing and evaluating signal models, filtering techniques, etc. In this thesis, the synthesized heartbeats are used to test the diagnostic distortion ...

Indoor location has experienced a major boost in recent years. location based services (LBS), which until recently were restricted to outdoor scenarios and the use of GPS, have also been extended into buildings. From large public structures such as airports or hospitals to a multitude of industrial scenarios, LBS has become increasingly present in indoor scenarios. Of the various technologies that can be used to achieve this indoor location, the ones based on ultra- wideband (UWB) signals have become ones of the most demanded due primarily to their accuracy in position estimation. Additionally, the appearance in the market of more and more manufacturers and products has lowered the prices of these devices to levels that allow to think about their use for large deployments with a contained budget. By their nature, UWB signals are very resistant to the multi-path phenomenon, ...

Future wireless networks will evolve to integrate communication, localization, and sensing capabilities. This evolution is driven by emerging application platforms such as digital twins, on the one hand, and advancements in wireless technologies, on the other, characterized by increased bandwidths, more antennas, and enhanced computational power. Crucial to this development is the application of artificial intelligence (AI), which is set to harness the vast amounts of available data in the sixth-generation (6G) of mobile networks and beyond. Integrating AI and machine learning (ML) algorithms, in particular, with wireless localization offers substantial opportunities to refine communication systems, improve the ability of wireless networks to locate the users precisely, enable context-aware transmission, and utilize processing and energy resources more efficiently. In this dissertation, advanced ML algorithms for enhanced wireless localization are proposed. Motivated by the capabilities of deep neural networks (DNNs) and ...

The number of biometric applications has increased a lot in the last few years. In this context, the automatic person recognition by some physical traits like fingerprints, face, voice or iris, plays an important role. Users demand this type of applications every time more and the technology seems already mature. People look for security, low cost and accuracy but, at the same time, there are many other factors in connection with biometric applications that are growing in importance. Intrusiveness is undoubtedly a burning factor to decide about the biometrics we will used for our application. At this point, one can realize about the suitability of speaker recognition because voice is the natural way of communicating, can be remotely used and provides a low cost. Automatic speaker recognition is commonly used in telephonic applications although it can also be used in ...