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

NASA Tech Briefs, August 2012

Topics covered include: Mars Science Laboratory Drill; Ultra-Compact Motor Controller; A Reversible Thermally Driven Pump for Use in a Sub-Kelvin Magnetic Refrigerator; Shape Memory Composite Hybrid Hinge; Binding Causes of Printed Wiring Assemblies with Card-Loks; Coring Sample Acquisition Tool; Joining and Assembly of Bulk Metallic Glass Composites Through Capacitive Discharge; 670-GHz Schottky Diode-Based Subharmonic Mixer with CPW Circuits and 70-GHz IF; Self-Nulling Lock-in Detection Electronics for Capacitance Probe Electrometer; Discontinuous Mode Power Supply; Optimal Dynamic Sub-Threshold Technique for Extreme Low Power Consumption for VLSI; Hardware for Accelerating N-Modular Redundant Systems for High-Reliability Computing; Blocking Filters with Enhanced Throughput for X-Ray Microcalorimetry; High-Thermal-Conductivity Fabrics; Imidazolium-Based Polymeric Materials as Alkaline Anion-Exchange Fuel Cell Membranes; Electrospun Nanofiber Coating of Fiber Materials: A Composite Toughening Approach; Experimental Modeling of Sterilization Effects for Atmospheric Entry Heating on Microorganisms; Saliva Preservative for Diagnostic Purposes; Hands-Free Transcranial Color Doppler Probe; Aerosol and Surface Parameter Retrievals for a Multi-Angle, Multiband Spectrometer LogScope; TraceContract; AIRS Maps from Space Processing Software; POSTMAN: Point of Sail Tacking for Maritime Autonomous Navigation; Space Operations Learning Center; OVERSMART Reporting Tool for Flow Computations Over Large Grid Systems; Large Eddy Simulation (LES) of Particle-Laden Temporal Mixing Layers; Projection of Stabilized Aerial Imagery Onto Digital Elevation Maps for Geo-Rectified and Jitter-Free Viewing; Iterative Transform Phase Diversity: An Image-Based Object and Wavefront Recovery; 3D Drop Size Distribution Extrapolation Algorithm Using a Single Disdrometer; Social Networking Adapted for Distributed Scientific Collaboration; General Methodology for Designing Spacecraft Trajectories; Hemispherical Field-of-View Above-Water Surface Imager for Submarines; and Quantum-Well Infrared Photodetector (QWIP) Focal Plane Assembly

Civilian Target Recognition using Hierarchical Fusion

The growth of computer vision technology has been marked by attempts to imitate human behavior to impart robustness and confidence to the decision making process of automated systems. Examples of disciplines in computer vision that have been targets of such efforts are Automatic Target Recognition (ATR) and fusion. ATR is the process of aided or unaided target detection and recognition using data from different sensors. Usually, it is synonymous with its military application of recognizing battlefield targets using imaging sensors. Fusion is the process of integrating information from different sources at the data or decision levels so as to provide a single robust decision as opposed to multiple individual results. This thesis combines these two research areas to provide improved classification accuracy in recognizing civilian targets. The results obtained reaffirm that fusion techniques tend to improve the recognition rates of ATR systems. Previous work in ATR has mainly dealt with military targets and single level of data fusion. Expensive sensors and time-consuming algorithms are generally used to improve system performance. In this thesis, civilian target recognition, which is considered to be harder than military target recognition, is performed. Inexpensive sensors are used to keep the system cost low. In order to compensate for the reduced system ability, fusion is performed at two different levels of the ATR system { event level and sensor level. Only preliminary image processing and pattern recognition techniques have been used so as to maintain low operation times. High classification rates are obtained using data fusion techniques alone. Another contribution of this thesis is the provision of a single framework to perform all operations from target data acquisition to the final decision making. The Sensor Fusion Testbed (SFTB) designed by Northrop Grumman Systems has been used by the Night Vision & Electronic Sensors Directorate to obtain images of seven different types of civilian targets. Image segmentation is performed using background subtraction. The seven invariant moments are extracted from the segmented image and basic classification is performed using k Nearest Neighbor method. Cross-validation is used to provide a better idea of the classification ability of the system. Temporal fusion at the event level is performed using majority voting and sensor level fusion is done using Behavior-Knowledge Space method. Two separate databases were used. The first database uses seven targets (2 cars, 2 SUVs, 2 trucks and 1 stake body light truck). Individual frame, temporal fusion and BKS fusion results are around 65%, 70% and 77% respectively. The second database has three targets (cars, SUVs and trucks) formed by combining classes from the first database. Higher classification accuracies are observed here. 75%, 90% and 95% recognition rates are obtained at frame, event and sensor levels. It can be seen that, on an average, recognition accuracy improves with increasing levels of fusion. Also, distance-based classification was performed to study the variation of system performance with the distance of the target from the cameras. The results are along expected lines and indicate the efficacy of fusion techniques for the ATR problem. Future work using more complex image processing and pattern recognition routines can further improve the classification performance of the system. The SFTB can be equipped with these algorithms and field-tested to check real-time performance

Ubiquitous computing and natural interfaces for environmental information

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do Grau de Mestre em Engenharia do Ambiente, perfil Gestão e Sistemas AmbientaisThe next computing revolution‘s objective is to embed every street, building, room and object with computational power. Ubiquitous computing (ubicomp) will allow every object to receive and transmit information, sense its surroundings and act accordingly, be located from anywhere in the world, connect every person. Everyone will have the possibility to access information, despite their age, computer knowledge, literacy or physical impairment. It will impact the world in a profound way, empowering mankind, improving the environment, but will also create new challenges that our society, economy, health and global environment will have to overcome. Negative impacts have to be identified and dealt with in advance. Despite these concerns, environmental studies have been mostly absent from discussions on the new paradigm. This thesis seeks to examine ubiquitous computing, its technological emergence, raise awareness towards future impacts and explore the design of new interfaces and rich interaction modes. Environmental information is approached as an area which may greatly benefit from ubicomp as a way to gather, treat and disseminate it, simultaneously complying with the Aarhus convention. In an educational context, new media are poised to revolutionize the way we perceive, learn and interact with environmental information. cUbiq is presented as a natural interface to access that information

The University Defence Research Collaboration In Signal Processing

This chapter describes the development of algorithms for automatic detection of anomalies from multi-dimensional, undersampled and incomplete datasets. The challenge in this work is to identify and classify behaviours as normal or abnormal, safe or threatening, from an irregular and often heterogeneous sensor network. Many defence and civilian applications can be modelled as complex networks of interconnected nodes with unknown or uncertain spatio-temporal relations. The behavior of such heterogeneous networks can exhibit dynamic properties, reflecting evolution in both network structure (new nodes appearing and existing nodes disappearing), as well as inter-node relations. The UDRC work has addressed not only the detection of anomalies, but also the identification of their nature and their statistical characteristics. Normal patterns and changes in behavior have been incorporated to provide an acceptable balance between true positive rate, false positive rate, performance and computational cost. Data quality measures have been used to ensure the models of normality are not corrupted by unreliable and ambiguous data. The context for the activity of each node in complex networks offers an even more efficient anomaly detection mechanism. This has allowed the development of efficient approaches which not only detect anomalies but which also go on to classify their behaviour

COBE's search for structure in the Big Bang

The launch of Cosmic Background Explorer (COBE) and the definition of Earth Observing System (EOS) are two of the major events at NASA-Goddard. The three experiments contained in COBE (Differential Microwave Radiometer (DMR), Far Infrared Absolute Spectrophotometer (FIRAS), and Diffuse Infrared Background Experiment (DIRBE)) are very important in measuring the big bang. DMR measures the isotropy of the cosmic background (direction of the radiation). FIRAS looks at the spectrum over the whole sky, searching for deviations, and DIRBE operates in the infrared part of the spectrum gathering evidence of the earliest galaxy formation. By special techniques, the radiation coming from the solar system will be distinguished from that of extragalactic origin. Unique graphics will be used to represent the temperature of the emitting material. A cosmic event will be modeled of such importance that it will affect cosmological theory for generations to come. EOS will monitor changes in the Earth's geophysics during a whole solar color cycle

Positioning of a wireless relay node for useful cooperative communication

Given the exorbitant amount of data transmitted and the increasing demand for data connectivity in the 21st century, it has become imperative to search for pro-active and sustainable solutions to the effectively alleviate the overwhelming burden imposed on wireless networks. In this study a Decode and Forward cooperative relay channel is analyzed, with the employment of Maximal Ratio Combining at the destination node as the method of offering diversity combining. The system framework used is based on a three-node relay channel with a source node, relay node and a destination node. A model for the wireless communications channel is formulated in order for simulation to be carried out to investigate the impact on performance of relaying on a node placed at the edge of cell. Firstly, an AWGN channel is used before the effect of Rayleigh fading is taken into consideration. Result shows that performance of cooperative relaying performance is always superior or similar to conventional relaying. Additionally, relaying is beneficial when the relay is placed closer to the receiver

Telemedicine

Telemedicine is a rapidly evolving field as new technologies are implemented for example for the development of wireless sensors, quality data transmission. Using the Internet applications such as counseling, clinical consultation support and home care monitoring and management are more and more realized, which improves access to high level medical care in underserved areas. The 23 chapters of this book present manifold examples of telemedicine treating both theoretical and practical foundations and application scenarios

Ayuda técnica para la autonomía en el desplazamiento

The project developed in this thesis involves the design, implementation and evaluation of a new technical assistance aiming to ease the mobility of people with visual impairments. By using processing and sounds synthesis, the users can hear the sonification protocol (through bone conduction) informing them, after training, about the position and distance of the various obstacles that may be on their way, avoiding eventual accidents. In this project, surveys were conducted with experts in the field of rehabilitation, blindness and techniques of image processing and sound, which defined the user requirements that served as guideline for the design. The thesis consists of three self-contained blocks: (i) image processing, where 4 processing algorithms are proposed for stereo vision, (ii) sonification, which details the proposed sound transformation of visual information, and (iii) a final central chapter on integrating the above and sequentially evaluated in two versions or implementation modes (software and hardware). Both versions have been tested with both sighted and blind participants, obtaining qualitative and quantitative results, which define future improvements to the project. ---------------------------------------------------------------------------------------------------------------------------------------------El proyecto desarrollado en la presente tesis doctoral consiste en el diseño, implementación y evaluación de una nueva ayuda técnica orientada a facilitar la movilidad de personas con discapacidad visual. El sistema propuesto consiste en un procesador de estereovisión y un sintetizador de sonidos, mediante los cuales, las usuarias y los usuarios pueden escuchar un código de sonidos mediante transmisión ósea que les informa, previo entrenamiento, de la posición y distancia de los distintos obstáculos que pueda haber en su camino, evitando accidentes. En dicho proyecto, se han realizado encuestas a expertos en el campo de la rehabilitación, la ceguera y en las técnicas y tecnologías de procesado de imagen y sonido, mediante las cuales se definieron unos requisitos de usuario que sirvieron como guía de propuesta y diseño. La tesis está compuesta de tres grandes bloques autocontenidos: (i) procesado de imagen, donde se proponen 4 algoritmos de procesado de visión estéreo, (ii) sonificación, en el cual se detalla la propuesta de transformación a sonido de la información visual, y (iii) un último capítulo central sobre integración de todo lo anterior en dos versiones evaluadas secuencialmente, una software y otra hardware. Ambas versiones han sido evaluadas con usuarios tanto videntes como invidentes, obteniendo resultados cualitativos y cuantitativos que permiten definir mejoras futuras sobre el proyecto finalmente implementado

Intelligent Circuits and Systems

ICICS-2020 is the third conference initiated by the School of Electronics and Electrical Engineering at Lovely Professional University that explored recent innovations of researchers working for the development of smart and green technologies in the fields of Energy, Electronics, Communications, Computers, and Control. ICICS provides innovators to identify new opportunities for the social and economic benefits of society.　 This conference bridges the gap between academics and R&D institutions, social visionaries, and experts from all strata of society to present their ongoing research activities and foster research relations between them. It provides opportunities for the exchange of new ideas, applications, and experiences in the field of smart technologies and finding global partners for future collaboration. The ICICS-2020 was conducted in two broad categories, Intelligent Circuits & Intelligent Systems and Emerging Technologies in Electrical Engineering