Vision Sensors and Edge Detection

Vision Sensors and Edge Detection book reflects a selection of recent developments within the area of vision sensors and edge detection. There are two sections in this book. The first section presents vision sensors with applications to panoramic vision sensors, wireless vision sensors, and automated vision sensor inspection, and the second one shows image processing techniques, such as, image measurements, image transformations, filtering, and parallel computing

Adaptive object segmentation and tracking

Efficient tracking of deformable objects moving with variable velocities is an important current research problem. In this thesis a robust tracking model is proposed for the automatic detection, recognition and tracking of target objects which are subject to variable orientations and velocities and are viewed under variable ambient lighting conditions. The tracking model can be applied to efficiently track fast moving vehicles and other objects in various complex scenarios. The tracking model is evaluated on both colour visible band and infra-red band video sequences acquired from the air by the Sussex police helicopter and other collaborators. The observations made validate the improved performance of the model over existing methods. The thesis is divided in three major sections. The first section details the development of an enhanced active contour for object segmentation. The second section describes an implementation of a global active contour orientation model. The third section describes the tracking model and assesses it performance on the aerial video sequences. In the first part of the thesis an enhanced active contour snake model using the difference of Gaussian (DoG) filter is reported and discussed in detail. An acquisition method based on the enhanced active contour method developed that can assist the proposed tracking system is tested. The active contour model is further enhanced by the use of a disambiguation framework designed to assist multiple object segmentation which is used to demonstrate that the enhanced active contour model can be used for robust multiple object segmentation and tracking. The active contour model developed not only facilitates the efficient update of the tracking filter but also decreases the latency involved in tracking targets in real-time. As far as computational effort is concerned, the active contour model presented improves the computational cost by 85% compared to existing active contour models. The second part of the thesis introduces the global active contour orientation (GACO) technique for statistical measurement of contoured object orientation. It is an overall object orientation measurement method which uses the proposed active contour model along with statistical measurement techniques. The use of the GACO technique, incorporating the active contour model, to measure object orientation angle is discussed in detail. A real-time door surveillance application based on the GACO technique is developed and evaluated on the i-LIDS door surveillance dataset provided by the UK Home Office. The performance results demonstrate the use of GACO to evaluate the door surveillance dataset gives a success rate of 92%. Finally, a combined approach involving the proposed active contour model and an optimal trade-off maximum average correlation height (OT-MACH) filter for tracking is presented. The implementation of methods for controlling the area of support of the OT-MACH filter is discussed in detail. The proposed active contour method as the area of support for the OT-MACH filter is shown to significantly improve the performance of the OT-MACH filter's ability to track vehicles moving within highly cluttered visible and infra-red band video sequence

Structural Health Monitoring for Composite Materials

Computer networking & communication

A Machine Learning-oriented Survey on Tiny Machine Learning

The emergence of Tiny Machine Learning (TinyML) has positively revolutionized the field of Artificial Intelligence by promoting the joint design of resource-constrained IoT hardware devices and their learning-based software architectures. TinyML carries an essential role within the fourth and fifth industrial revolutions in helping societies, economies, and individuals employ effective AI-infused computing technologies (e.g., smart cities, automotive, and medical robotics). Given its multidisciplinary nature, the field of TinyML has been approached from many different angles: this comprehensive survey wishes to provide an up-to-date overview focused on all the learning algorithms within TinyML-based solutions. The survey is based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodological flow, allowing for a systematic and complete literature survey. In particular, firstly we will examine the three different workflows for implementing a TinyML-based system, i.e., ML-oriented, HW-oriented, and co-design. Secondly, we propose a taxonomy that covers the learning panorama under the TinyML lens, examining in detail the different families of model optimization and design, as well as the state-of-the-art learning techniques. Thirdly, this survey will present the distinct features of hardware devices and software tools that represent the current state-of-the-art for TinyML intelligent edge applications. Finally, we discuss the challenges and future directions.Comment: Article currently under review at IEEE Acces

Polifemo Device Business Plan

Spacecrafts continuously need for low cost and weight sensor easy to integrate in a plug-in approach and capable to improve platforms versatility while reducing integration time and complexity. This is particularly true for the new generation of small and micro satellites to be launched in constellation and formation. Controlling small satellites cooperation and protecting the space assets from debris are two important issues of current and future missions. The cost reduction and safety of space missions is a key issue for further expand European leadership in the Earth Observation and Communication sectors. The POLIFEMO (Panoramic Multifunctional Sensor for Small/Micro Satellite) is a unique solution for an integrated sensor capable to replace by one single unit the functions of Sun sensor, Earth sensor and Star tracker and, additionally, providing external situational awareness. POLIFEMO is based on an innovative lens with a very wide angle (with a hyper-hemispheric field of view) able to look at a field of view of 360 in azimuth (panoramic omnidirectional lens) and 270 in elevation (hyper-hemispheric capabilities), designed and patented by the Italian National Institute for Astrophysics (INAF). POLIFEMO, with that extremely high field of view and unique imaging detection capability, results in a small, low weight, low cost and reliable (no moving part, potentially failure point) space sensor. It is unique in the market of space sensors and suitable for many spaces and non-space missions (e.g., communication, weather, imaging, surveillance, deep space but also UAV/HAP). Progetti Speciali Italiani s.r.l., a SME active in developing microsatellite and space applications, has set up, during the phase 1 project, a very experienced team of engineering and commercial specialists for carrying on the proposed project. University of Napoli (Parthenope) is expert on developing satellites star trackers solutions. This paper reports a summary extracted from a more detailed BP (Doc: ECSME-PSI-POLIFEMO-BP-2016) which has been prepared within the EU-H2020 contract framework. The full BP is available on request

INFLAMMATORY INTERACTIONS AND SECRETION IN CARDIAC REMODELING

Heart failure contributes to nearly 60,000 deaths per year in the USA and is often caused by hypertension and preceded by the development of left ventricular hypertrophy (LVH). LVH is usually accompanied by intensive interstitial and perivascular fibrosis which may contribute to arrhythmogenic sudden cardiac death. Emerging evidence indicates that LV dysfunction in patients and animal models of cardiac hypertrophy is closely associated with perivascular inflammation. To investigate the role of perivascular inflammation in coronary artery remodeling and cardiac fibrosis during hypertrophic ventricular remodeling, we used a well-established mouse model of pressure-overload-induced LVH: transverse aortic constriction (TAC). Early perivascular inflammation was indicated by accumulation of macrophages and T lymphocytes 24 hours post-TAC and which peaked at day 7. Coronary luminal platelet deposition was observed along with macrophages and lymphocytes at day 3. Also, LV protein levels of VEGF and MCP-1 were significantly increased. Consistent with lymphocyte accumulation, cardiac expression of IL-10 mRNA was elevated. Furthermore, circulating platelet-leukocyte aggregates tended to be higher after TAC, compared to sham controls. Platelets have been shown to modulate perivascular inflammation and may facilitate leukocyte recruitment at sites of inflamed endothelium. Therefore, we investigated the impact of thrombocytopenia in the response to TAC. Immunodepletion of platelets decreased early perivascular accumulation of T lymphocytes and IL-10 mRNA expression, and altered subsequent coronary artery remodeling. The contribution of lymphocytes was examined in Rag1-/- mice, which displayed significantly more intimal hyperplasia and perivascular fibrosis compared to wild-type mice following TAC. Collectively, our studies support a role of early perivascular accumulation of platelets and T lymphocytes in pressure overload-induced inflammation which will contribute to long-term LV remodeling. One potential mechanism for inflammatory cells to modulate their environment and affect surrounding cells is through release of cargo stored in granules. To determine the contribution of granule release from inflammatory cells in the development of LVH, we used Unc13dJinx (Jinx) mice, which contain a single point mutation in Unc13d gene resulting in defects in Munc13-4. Munc13-4 is a limiting factor in vesicular priming and fusion during granule secretion. Therefore, Jinx mice have defects in degranulation of platelets, NK cells, cytotoxic T lymphocytes, neutrophils, mast and other cells. With the use of bone marrow transplantation, Jinx chimeric mice were created to determine whether the ability of hematopoietic cells to secrete granule contents affects the development of LVH. Wild-type mice (WT) that were transplanted with WT bone marrow (WT\u3eWT) and WT mice that received Jinx bone marrow (Jinx\u3eWT) developed LVH and a classic fetal reprogramming response early after TAC (7 days), but at later times (5 weeks), Jinx\u3eWT mice failed to sustain the cardiac hypertrophic response observed in WT\u3eWT mice. No difference in cardiac fibrosis was observed at early or late times. Repetitive injection of WT platelets or platelet releasate restored cardiac hypertrophy in Jinx\u3eWT mice. These results suggest that sustained LVH in the setting of pressure overload depends on factor(s) secreted, likely from platelets. In conclusion, our studies demonstrate that platelets and lymphocytes are involved in early perivascular inflammation post-TAC, which may contribute to later remodeling in the setting of LVH. Factors released from hematopoietic cells, including platelets, in a Munc13-4-dependent manner are required to promote cardiac hypertrophy. These findings focus attention on modulating perivascular inflammation and targeting granule cargo release to prevent the development and consequences of LVH

Particle Swarm Optimization

Particle swarm optimization (PSO) is a population based stochastic optimization technique influenced by the social behavior of bird flocking or fish schooling.PSO shares many similarities with evolutionary computation techniques such as Genetic Algorithms (GA). The system is initialized with a population of random solutions and searches for optima by updating generations. However, unlike GA, PSO has no evolution operators such as crossover and mutation. In PSO, the potential solutions, called particles, fly through the problem space by following the current optimum particles. This book represents the contributions of the top researchers in this field and will serve as a valuable tool for professionals in this interdisciplinary field

Sparse Signal Representation of Ultrasonic Signals for Structural Health Monitoring Applications

Assessment of the integrity of structural components is of great importance for aerospace systems, land and marine transportation, civil infrastructures and other biological and mechanical applications. Guided waves (GWs) based inspections are an attractive mean for structural health monitoring. In this thesis, the study and development of techniques for GW ultrasound signal analysis and compression in the context of non-destructive testing of structures will be presented. In guided wave inspections, it is necessary to address the problem of the dispersion compensation. A signal processing approach based on frequency warping was adopted. Such operator maps the frequencies axis through a function derived by the group velocity of the test material and it is used to remove the dependence on the travelled distance from the acquired signals. Such processing strategy was fruitfully applied for impact location and damage localization tasks in composite and aluminum panels. It has been shown that, basing on this processing tool, low power embedded system for GW structural monitoring can be implemented. Finally, a new procedure based on Compressive Sensing has been developed and applied for data reduction. Such procedure has also a beneficial effect in enhancing the accuracy of structural defects localization. This algorithm uses the convolutive model of the propagation of ultrasonic guided waves which takes advantage of a sparse signal representation in the warped frequency domain. The recovery from the compressed samples is based on an alternating minimization procedure which achieves both an accurate reconstruction of the ultrasonic signal and a precise estimation of waves time of flight. Such information is used to feed hyperbolic or elliptic localization procedures, for accurate impact or damage localization

Patient Specific Systems for Computer Assisted Robotic Surgery Simulation, Planning, and Navigation

The evolving scenario of surgery: starting from modern surgery, to the birth of medical imaging and the introduction of minimally invasive techniques, has seen in these last years the advent of surgical robotics. These systems, making possible to get through the difficulties of endoscopic surgery, allow an improved surgical performance and a better quality of the intervention. Information technology contributed to this evolution since the beginning of the digital revolution: providing innovative medical imaging devices and computer assisted surgical systems. Afterwards, the progresses in computer graphics brought innovative visualization modalities for medical datasets, and later the birth virtual reality has paved the way for virtual surgery. Although many surgical simulators already exist, there are no patient specific solutions. This thesis presents the development of patient specific software systems for preoperative planning, simulation and intraoperative assistance, designed for robotic surgery: in particular for bimanual robots that are becoming the future of single port interventions. The first software application is a virtual reality simulator for this kind of surgical robots. The system has been designed to validate the initial port placement and the operative workspace for the potential application of this surgical device. Given a bimanual robot with its own geometry and kinematics, and a patient specific 3D virtual anatomy, the surgical simulator allows the surgeon to choose the optimal positioning of the robot and the access port in the abdominal wall. Additionally, it makes possible to evaluate in a virtual environment if a dexterous movability of the robot is achievable, avoiding unwanted collisions with the surrounding anatomy to prevent potential damages in the real surgical procedure. Even if the software has been designed for a specific bimanual surgical robot, it supports any open kinematic chain structure: as far as it can be described in our custom format. The robot capabilities to accomplish specific tasks can be virtually tested using the deformable models: interacting directly with the target virtual organs, trying to avoid unwanted collisions with the surrounding anatomy not involved in the intervention. Moreover, the surgical simulator has been enhanced with algorithms and data structures to integrate biomechanical parameters into virtual deformable models (based on mass-spring-damper network) of target solid organs, in order to properly reproduce the physical behaviour of the patient anatomy during the interactions. The main biomechanical parameters (Young's modulus and density) have been integrated, allowing the automatic tuning of some model network elements, such as: the node mass and the spring stiffness. The spring damping coefficient has been modeled using the Rayleigh approach. Furthermore, the developed method automatically detect the external layer, allowing the usage of both the surface and internal Young's moduli, in order to model the main parts of dense organs: the stroma and the parenchyma. Finally the model can be manually tuned to represent lesion with specific biomechanical properties. Additionally, some software modules of the simulator have been properly extended to be integrated in a patient specific computer guidance system for intraoperative navigation and assistance in robotic single port interventions. This application provides guidance functionalities working in three different modalities: passive as a surgical navigator, assistive as a guide for the single port placement and active as a tutor preventing unwanted collision during the intervention. The simulation system has beed tested by five surgeons: simulating the robot access port placemen, and evaluating the robot movability and workspace inside the patient abdomen. The tested functionalities, rated by expert surgeons, have shown good quality and performance of the simulation. Moreover, the integration of biomechanical parameters into deformable models has beed tested with various material samples. The results have shown a good visual realism ensuring the performance required by an interactive simulation. Finally, the intraoperative navigator has been tested performing a cholecystectomy on a synthetic patient mannequin, in order to evaluate: the intraoperative navigation accuracy, the network communications latency and the overall usability of the system. The tests performed demonstrated the effectiveness and the usability of the software systems developed: encouraging the introduction of the proposed solution in the clinical practice, and the implementation of further improvements. Surgical robotics will be enhanced by an advanced integration of medical images into software systems: allowing the detailed planning of surgical interventions by means of virtual surgery simulation based on patient specific biomechanical parameters. Furthermore, the advanced functionalities offered by these systems, enable surgical robots to improve the intraoperative surgical assistance: benefitting of the knowledge of the virtual patient anatomy