Sistema de aquisição de dados para estudos de transiente de pressão e detecção de vazamentos em oleodutos

In February 2011, the National Agency of Petroleum, Natural Gas and Biofuels (ANP) has published a new Technical Rules for Handling Land Pipeline Petroleum and Natural Gas Derivatives (RTDT). Among other things, the RTDT made compulsory the use of monitoring systems and leak detection in all onshore pipelines in the country. This document provides a study on the method for detection of transient pressure. The study was conducted on a industrial duct 16" diameter and 9.8 km long. The pipeline is fully pressurized and carries a multiphase mixture of crude oil, water and natural gas. For the study, was built an infrastructure for data acquisition and validation of detection algorithms. The system was designed with SCADA architecture. Piezoresistive sensors were installed at the ends of the duct and Digital Signal Processors (DSPs) were used for sampling, storage and processing of data. The study was based on simulations of leaks through valves and search for patterns that characterize the occurrence of such phenomena

Otimização de processos semi-automáticos de detecção de alterações aplicadas ao cadastro imobiliário

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Algoritmos de detecção de bordas implementados em FPGA

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Sistema de detecção automática on-line de danos térmicos no processo de retificação com monitoramento via internet

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

The NINJA-2 project: detecting and characterizing gravitational waveforms modelled using numerical binary black hole simulations

The Numerical INJection Analysis (NINJA) project is a collaborative effort between members of the numerical relativity and gravitational-wave (GW) astrophysics communities. The purpose of NINJA is to study the ability to detect GWs emitted from merging binary black holes (BBH) and recover their parameters with next-generation GW observatories. We report here on the results of the second NINJA project, NINJA-2, which employs 60 complete BBH hybrid waveforms consisting of a numerical portion modelling the late inspiral, merger, and ringdown stitched to a post-Newtonian portion modelling the early inspiral. In a 'blind injection challenge' similar to that conducted in recent Laser Interferometer Gravitational Wave Observatory (LIGO) and Virgo science runs, we added seven hybrid waveforms to two months of data recoloured to predictions of Advanced LIGO (aLIGO) and Advanced Virgo (AdV) sensitivity curves during their first observing runs. The resulting data was analysed by GW detection algorithms and 6 of the waveforms were recovered with false alarm rates smaller than 1 in a thousand years. Parameter-estimation algorithms were run on each of these waveforms to explore the ability to constrain the masses, component angular momenta and sky position of these waveforms. We find that the strong degeneracy between the mass ratio and the BHs' angular momenta will make it difficult to precisely estimate these parameters with aLIGO and AdV. We also perform a large-scale Monte Carlo study to assess the ability to recover each of the 60 hybrid waveforms with early aLIGO and AdV sensitivity curves. Our results predict that early aLIGO and AdV will have a volume-weighted average sensitive distance of 300 Mpc (1 Gpc) for 10M circle dot + 10M circle dot (50M circle dot + 50M circle dot) BBH coalescences. We demonstrate that neglecting the component angular momenta in the waveform models used in matched-filtering will result in a reduction in sensitivity for systems with large component angular momenta. This reduction is estimated to be up to similar to 15% for 50M circle dot + 50M circle dot BBH coalescences with almost maximal angular momenta aligned with the orbit when using early aLIGO and AdV sensitivity curves.

Segurança em redes sem fio: estudo sobre o desenvolvimento de conjuntos de dados para comparação de IDS

Pós-graduação em Engenharia Elétrica - FEIS

A complex networks approach for data clustering

This work proposes a method for data clustering based on complex networks theory. A data set is represented as a network by considering different metrics to establish the connection between each pair of objects. The clusters are obtained by taking into account five community detection algorithms. The network-based clustering approach is applied in two real-world databases and two sets of artificially generated data. The obtained results suggest that the exponential of the Minkowski distance is the most suitable metric to quantify the similarities between pairs of objects. In addition, the community identification method based on the greedy optimization provides the best cluster solution. We compare the network-based clustering approach with some traditional clustering algorithms and verify that it provides the lowest classification error rate. (C) 2012 Elsevier B.V. All rights reserved.

Content extraction: Identifying the main content in HTML documents

Except the article forming the main content most HTML documents on the WWW contain additional contents such as navigation menus, design elements or commercial banners. In the context of several applications it is necessary to draw the distinction between main and additional content automatically. Content extraction and template detection are the two approaches to solve this task. This thesis gives an extensive overview of existing algorithms from both areas. It contributes an objective way to measure and evaluate the performance of content extraction algorithms under different aspects. These evaluation measures allow to draw the first objective comparison of existing extraction solutions. The newly introduced content code blurring algorithm overcomes several drawbacks of previous approaches and proves to be the best content extraction algorithm at the moment. An analysis of methods to cluster web documents according to their underlying templates is the third major contribution of this thesis. In combination with a localised crawling process this clustering analysis can be used to automatically create sets of training documents for template detection algorithms. As the whole process can be automated it allows to perform template detection on a single document, thereby combining the advantages of single and multi document algorithms.

Efficient parallel proximity queries and an application to highly complex motion planning problems with many narrow passages

In vielen Bereichen der industriellen Fertigung, wie zum Beispiel in der Automobilindustrie, wer- den digitale Versuchsmodelle (sog. digital mock-ups) eingesetzt, um die Entwicklung komplexer Maschinen m ̈oglichst gut durch Computersysteme unterstu ̈tzen zu k ̈onnen. Hierbei spielen Be- wegungsplanungsalgorithmen eine wichtige Rolle, um zu gew ̈ahrleisten, dass diese digitalen Pro- totypen auch kollisionsfrei zusammengesetzt werden k ̈onnen. In den letzten Jahrzehnten haben sich hier sampling-basierte Verfahren besonders bew ̈ahrt. Diese erzeugen eine große Anzahl von zuf ̈alligen Lagen fu ̈r das ein-/auszubauende Objekt und verwenden einen Kollisionserken- nungsmechanismus, um die einzelnen Lagen auf Gu ̈ltigkeit zu u ̈berpru ̈fen. Daher spielt die Kollisionserkennung eine wesentliche Rolle beim Design effizienter Bewegungsplanungsalgorith- men. Eine Schwierigkeit fu ̈r diese Klasse von Planern stellen sogenannte “narrow passages” dar, schmale Passagen also, die immer dort auftreten, wo die Bewegungsfreiheit der zu planenden Objekte stark eingeschr ̈ankt ist. An solchen Stellen kann es schwierig sein, eine ausreichende Anzahl von kollisionsfreien Samples zu finden. Es ist dann m ̈oglicherweise n ̈otig, ausgeklu ̈geltere Techniken einzusetzen, um eine gute Performance der Algorithmen zu erreichen.rnDie vorliegende Arbeit gliedert sich in zwei Teile: Im ersten Teil untersuchen wir parallele Kollisionserkennungsalgorithmen. Da wir auf eine Anwendung bei sampling-basierten Bewe- gungsplanern abzielen, w ̈ahlen wir hier eine Problemstellung, bei der wir stets die selben zwei Objekte, aber in einer großen Anzahl von unterschiedlichen Lagen auf Kollision testen. Wir im- plementieren und vergleichen verschiedene Verfahren, die auf Hu ̈llk ̈operhierarchien (BVHs) und hierarchische Grids als Beschleunigungsstrukturen zuru ̈ckgreifen. Alle beschriebenen Verfahren wurden auf mehreren CPU-Kernen parallelisiert. Daru ̈ber hinaus vergleichen wir verschiedene CUDA Kernels zur Durchfu ̈hrung BVH-basierter Kollisionstests auf der GPU. Neben einer un- terschiedlichen Verteilung der Arbeit auf die parallelen GPU Threads untersuchen wir hier die Auswirkung verschiedener Speicherzugriffsmuster auf die Performance der resultierenden Algo- rithmen. Weiter stellen wir eine Reihe von approximativen Kollisionstests vor, die auf den beschriebenen Verfahren basieren. Wenn eine geringere Genauigkeit der Tests tolerierbar ist, kann so eine weitere Verbesserung der Performance erzielt werden.rnIm zweiten Teil der Arbeit beschreiben wir einen von uns entworfenen parallelen, sampling- basierten Bewegungsplaner zur Behandlung hochkomplexer Probleme mit mehreren “narrow passages”. Das Verfahren arbeitet in zwei Phasen. Die grundlegende Idee ist hierbei, in der er- sten Planungsphase konzeptionell kleinere Fehler zuzulassen, um die Planungseffizienz zu erh ̈ohen und den resultierenden Pfad dann in einer zweiten Phase zu reparieren. Der hierzu in Phase I eingesetzte Planer basiert auf sogenannten Expansive Space Trees. Zus ̈atzlich haben wir den Planer mit einer Freidru ̈ckoperation ausgestattet, die es erlaubt, kleinere Kollisionen aufzul ̈osen und so die Effizienz in Bereichen mit eingeschr ̈ankter Bewegungsfreiheit zu erh ̈ohen. Optional erlaubt unsere Implementierung den Einsatz von approximativen Kollisionstests. Dies setzt die Genauigkeit der ersten Planungsphase weiter herab, fu ̈hrt aber auch zu einer weiteren Perfor- mancesteigerung. Die aus Phase I resultierenden Bewegungspfade sind dann unter Umst ̈anden nicht komplett kollisionsfrei. Um diese Pfade zu reparieren, haben wir einen neuartigen Pla- nungsalgorithmus entworfen, der lokal beschr ̈ankt auf eine kleine Umgebung um den bestehenden Pfad einen neuen, kollisionsfreien Bewegungspfad plant.rnWir haben den beschriebenen Algorithmus mit einer Klasse von neuen, schwierigen Metall- Puzzlen getestet, die zum Teil mehrere “narrow passages” aufweisen. Unseres Wissens nach ist eine Sammlung vergleichbar komplexer Benchmarks nicht ̈offentlich zug ̈anglich und wir fan- den auch keine Beschreibung von vergleichbar komplexen Benchmarks in der Motion-Planning Literatur.

An Instrument Design for Space-Based Optical Observation of Space Debris

Currently, observations of space debris are primarily performed with ground-based sensors. These sensors have a detection limit at some centimetres diameter for objects in Low Earth Orbit (LEO) and at about two decimetres diameter for objects in Geostationary Orbit (GEO). The few space-based debris observations stem mainly from in-situ measurements and from the analysis of returned spacecraft surfaces. Both provide information about mostly sub-millimetre-sized debris particles. As a consequence the population of centimetre- and millimetre-sized debris objects remains poorly understood. The development, validation and improvement of debris reference models drive the need for measurements covering the whole diameter range. In 2003 the European Space Agency (ESA) initiated a study entitled “Space-Based Optical Observation of Space Debris”. The first tasks of the study were to define user requirements and to develop an observation strategy for a space-based instrument capable of observing uncatalogued millimetre-sized debris objects. Only passive optical observations were considered, focussing on mission concepts for the LEO, and GEO regions respectively. Starting from the requirements and the observation strategy, an instrument system architecture and an associated operations concept have been elaborated. The instrument system architecture covers the telescope, camera and onboard processing electronics. The proposed telescope is a folded Schmidt design, characterised by a 20 cm aperture and a large field of view of 6°. The camera design is based on the use of either a frame-transfer charge coupled device (CCD), or on a cooled hybrid sensor with fast read-out. A four megapixel sensor is foreseen. For the onboard processing, a scalable architecture has been selected. Performance simulations have been executed for the system as designed, focussing on the orbit determination of observed debris particles, and on the analysis of the object detection algorithms. In this paper we present some of the main results of the study. A short overview of the user requirements and observation strategy is given. The architectural design of the instrument is discussed, and the main tradeoffs are outlined. An insight into the results of the performance simulations is provided.

Skin Lesion Extraction And Its Application

In this thesis, I study skin lesion detection and its applications to skin cancer diagnosis. A skin lesion detection algorithm is proposed. The proposed algorithm is based color information and threshold. For the proposed algorithm, several color spaces are studied and the detection results are compared. Experimental results show that YUV color space can achieve the best performance. Besides, I develop a distance histogram based threshold selection method and the method is proven to be better than other adaptive threshold selection methods for color detection. Besides the detection algorithms, I also investigate GPU speed-up techniques for skin lesion extraction and the results show that GPU has potential applications in speeding-up skin lesion extraction. Based on the skin lesion detection algorithms proposed, I developed a mobile-based skin cancer diagnosis application. In this application, the user with an iPhone installed with the proposed application can use the iPhone as a diagnosis tool to find the potential skin lesions in a persons' skin and compare the skin lesions detected by the iPhone with the skin lesions stored in a database in a remote server.

A practical approach to designing syndromic surveillance systems for livestock and poultry

The field of animal syndromic surveillance (SyS) is growing, with many systems being developed worldwide. Now is an appropriate time to share ideas and lessons learned from early SyS design and implementation. Based on our practical experience in animal health SyS, with additions from the public health and animal health SyS literature, we put forward for discussion a 6-step approach to designing SyS systems for livestock and poultry. The first step is to formalise policy and surveillance goals which are considerate of stakeholder expectations and reflect priority issues (1). Next, it is important to find consensus on national priority diseases and identify current surveillance gaps. The geographic, demographic, and temporal coverage of the system must be carefully assessed (2). A minimum dataset for SyS that includes the essential data to achieve all surveillance objectives while minimizing the amount of data collected should be defined. One can then compile an inventory of the data sources available and evaluate each using the criteria developed (3). A list of syndromes should then be produced for all data sources. Cases can be classified into syndrome classes and the data can be converted into time series (4). Based on the characteristics of the syndrome-time series, the length of historic data available and the type of outbreaks the system must detect, different aberration detection algorithms can be tested (5). Finally, it is essential to develop a minimally acceptable response protocol for each statistical signal produced (6). Important outcomes of this pre-operational phase should be building of a national network of experts and collective action and evaluation plans. While some of the more applied steps (4 and 5) are currently receiving consideration, more emphasis should be put on earlier conceptual steps by decision makers and surveillance developers (1-3).

Investigating the potential of reported cattle mortality data in Switzerland for syndromic surveillance

Systems for the identification and registration of cattle have gradually been receiving attention for use in syndromic surveillance, a relatively recent approach for the early detection of infectious disease outbreaks. Real or near real-time monitoring of deaths or stillbirths reported to these systems offer an opportunity to detect temporal or spatial clusters of increased mortality that could be caused by an infectious disease epidemic. In Switzerland, such data are recorded in the "Tierverkehrsdatenbank" (TVD). To investigate the potential of the Swiss TVD for syndromic surveillance, 3 years of data (2009-2011) were assessed in terms of data quality, including timeliness of reporting and completeness of geographic data. Two time-series consisting of reported on-farm deaths and stillbirths were retrospectively analysed to define and quantify the temporal patterns that result from non-health related factors. Geographic data were almost always present in the TVD data; often at different spatial scales. On-farm deaths were reported to the database by farmers in a timely fashion; stillbirths were less timely. Timeliness and geographic coverage are two important features of disease surveillance systems, highlighting the suitability of the TVD for use in a syndromic surveillance system. Both time series exhibited different temporal patterns that were associated with non-health related factors. To avoid false positive signals, these patterns need to be removed from the data or accounted for in some way before applying aberration detection algorithms in real-time. Evaluating mortality data reported to systems for the identification and registration of cattle is of value for comparing national data systems and as a first step towards a European-wide early detection system for emerging and re-emerging cattle diseases.

Design and control of multi-finger haptic devices for dexterous manipulation

En la interacción con el entorno que nos rodea durante nuestra vida diaria (utilizar un cepillo de dientes, abrir puertas, utilizar el teléfono móvil, etc.) y en situaciones profesionales (intervenciones médicas, procesos de producción, etc.), típicamente realizamos manipulaciones avanzadas que incluyen la utilización de los dedos de ambas manos. De esta forma el desarrollo de métodos de interacción háptica multi-dedo dan lugar a interfaces hombre-máquina más naturales y realistas. No obstante, la mayoría de interfaces hápticas disponibles en el mercado están basadas en interacciones con un solo punto de contacto; esto puede ser suficiente para la exploración o palpación del entorno pero no permite la realización de tareas más avanzadas como agarres. En esta tesis, se investiga el diseño mecánico, control y aplicaciones de dispositivos hápticos modulares con capacidad de reflexión de fuerzas en los dedos índice, corazón y pulgar del usuario. El diseño mecánico de la interfaz diseñada, ha sido optimizado con funciones multi-objetivo para conseguir una baja inercia, un amplio espacio de trabajo, alta manipulabilidad y reflexión de fuerzas superiores a 3 N en el espacio de trabajo. El ancho de banda y la rigidez del dispositivo se han evaluado mediante simulación y experimentación real. Una de las áreas más importantes en el diseño de estos dispositivos es el efector final, ya que es la parte que está en contacto con el usuario. Durante este trabajo se ha diseñado un dedal de bajo peso, adaptable a diferentes usuarios que, mediante la incorporación de sensores de contacto, permite estimar fuerzas normales y tangenciales durante la interacción con entornos reales y virtuales. Para el diseño de la arquitectura de control, se estudiaron los principales requisitos para estos dispositivos. Entre estos, cabe destacar la adquisición, procesado e intercambio a través de internet de numerosas señales de control e instrumentación; la computación de equaciones matemáticas incluyendo la cinemática directa e inversa, jacobiana, algoritmos de detección de agarres, etc. Todos estos componentes deben calcularse en tiempo real garantizando una frecuencia mínima de 1 KHz. Además, se describen sistemas para manipulación de precisión virtual y remota; así como el diseño de un método denominado "desacoplo cinemático iterativo" para computar la cinemática inversa de robots y la comparación con otros métodos actuales. Para entender la importancia de la interacción multimodal, se ha llevado a cabo un estudio para comprobar qué estímulos sensoriales se correlacionan con tiempos de respuesta más rápidos y de mayor precisión. Estos experimentos se desarrollaron en colaboración con neurocientíficos del instituto Technion Israel Institute of Technology. Comparando los tiempos de respuesta en la interacción unimodal (auditiva, visual y háptica) con combinaciones bimodales y trimodales de los mismos, se demuestra que el movimiento sincronizado de los dedos para generar respuestas de agarre se basa principalmente en la percepción háptica. La ventaja en el tiempo de procesamiento de los estímulos hápticos, sugiere que los entornos virtuales que incluyen esta componente sensorial generan mejores contingencias motoras y mejoran la credibilidad de los eventos. Se concluye que, los sistemas que incluyen percepción háptica dotan a los usuarios de más tiempo en las etapas cognitivas para rellenar información de forma creativa y formar una experiencia más rica. Una aplicación interesante de los dispositivos hápticos es el diseño de nuevos simuladores que permitan entrenar habilidades manuales en el sector médico. En colaboración con fisioterapeutas de Griffith University en Australia, se desarrolló un simulador que permite realizar ejercicios de rehabilitación de la mano. Las propiedades de rigidez no lineales de la articulación metacarpofalange del dedo índice se estimaron mediante la utilización del efector final diseñado. Estos parámetros, se han implementado en un escenario que simula el comportamiento de la mano humana y que permite la interacción háptica a través de esta interfaz. Las aplicaciones potenciales de este simulador están relacionadas con entrenamiento y educación de estudiantes de fisioterapia. En esta tesis, se han desarrollado nuevos métodos que permiten el control simultáneo de robots y manos robóticas en la interacción con entornos reales. El espacio de trabajo alcanzable por el dispositivo háptico, se extiende mediante el cambio de modo de control automático entre posición y velocidad. Además, estos métodos permiten reconocer el gesto del usuario durante las primeras etapas de aproximación al objeto para su agarre. Mediante experimentos de manipulación avanzada de objetos con un manipulador y diferentes manos robóticas, se muestra que el tiempo en realizar una tarea se reduce y que el sistema permite la realización de la tarea con precisión. Este trabajo, es el resultado de una colaboración con investigadores de Harvard BioRobotics Laboratory. ABSTRACT When we interact with the environment in our daily life (using a toothbrush, opening doors, using cell-phones, etc.), or in professional situations (medical interventions, manufacturing processes, etc.) we typically perform dexterous manipulations that involve multiple fingers and palm for both hands. Therefore, multi-Finger haptic methods can provide a realistic and natural human-machine interface to enhance immersion when interacting with simulated or remote environments. Most commercial devices allow haptic interaction with only one contact point, which may be sufficient for some exploration or palpation tasks but are not enough to perform advanced object manipulations such as grasping. In this thesis, I investigate the mechanical design, control and applications of a modular haptic device that can provide force feedback to the index, thumb and middle fingers of the user. The designed mechanical device is optimized with a multi-objective design function to achieve a low inertia, a large workspace, manipulability, and force-feedback of up to 3 N within the workspace; the bandwidth and rigidity for the device is assessed through simulation and real experimentation. One of the most important areas when designing haptic devices is the end-effector, since it is in contact with the user. In this thesis the design and evaluation of a thimble-like, lightweight, user-adaptable, and cost-effective device that incorporates four contact force sensors is described. This design allows estimation of the forces applied by a user during manipulation of virtual and real objects. The design of a real-time, modular control architecture for multi-finger haptic interaction is described. Requirements for control of multi-finger haptic devices are explored. Moreover, a large number of signals have to be acquired, processed, sent over the network and mathematical computations such as device direct and inverse kinematics, jacobian, grasp detection algorithms, etc. have to be calculated in Real Time to assure the required high fidelity for the haptic interaction. The Hardware control architecture has different modules and consists of an FPGA for the low-level controller and a RT controller for managing all the complex calculations (jacobian, kinematics, etc.); this provides a compact and scalable solution for the required high computation capabilities assuring a correct frequency rate for the control loop of 1 kHz. A set-up for dexterous virtual and real manipulation is described. Moreover, a new algorithm named the iterative kinematic decoupling method was implemented to solve the inverse kinematics of a robotic manipulator. In order to understand the importance of multi-modal interaction including haptics, a subject study was carried out to look for sensory stimuli that correlate with fast response time and enhanced accuracy. This experiment was carried out in collaboration with neuro-scientists from Technion Israel Institute of Technology. By comparing the grasping response times in unimodal (auditory, visual, and haptic) events with the response times in events with bimodal and trimodal combinations. It is concluded that in grasping tasks the synchronized motion of the fingers to generate the grasping response relies on haptic cues. This processing-speed advantage of haptic cues suggests that multimodalhaptic virtual environments are superior in generating motor contingencies, enhancing the plausibility of events. Applications that include haptics provide users with more time at the cognitive stages to fill in missing information creatively and form a richer experience. A major application of haptic devices is the design of new simulators to train manual skills for the medical sector. In collaboration with physical therapists from Griffith University in Australia, we developed a simulator to allow hand rehabilitation manipulations. First, the non-linear stiffness properties of the metacarpophalangeal joint of the index finger were estimated by using the designed end-effector; these parameters are implemented in a scenario that simulates the behavior of the human hand and that allows haptic interaction through the designed haptic device. The potential application of this work is related to educational and medical training purposes. In this thesis, new methods to simultaneously control the position and orientation of a robotic manipulator and the grasp of a robotic hand when interacting with large real environments are studied. The reachable workspace is extended by automatically switching between rate and position control modes. Moreover, the human hand gesture is recognized by reading the relative movements of the index, thumb and middle fingers of the user during the early stages of the approximation-to-the-object phase and then mapped to the robotic hand actuators. These methods are validated to perform dexterous manipulation of objects with a robotic manipulator, and different robotic hands. This work is the result of a research collaboration with researchers from the Harvard BioRobotics Laboratory. The developed experiments show that the overall task time is reduced and that the developed methods allow for full dexterity and correct completion of dexterous manipulations.

Detección de patrones y anomalías espectrales del terreno mediante espectrometría de imagen de alta resolución : reconocimiento, optimización y evaluación multiescenario

El objeto de esta Tesis doctoral es el desarrollo de una metodologia para la deteccion automatica de anomalias a partir de datos hiperespectrales o espectrometria de imagen, y su cartografiado bajo diferentes condiciones tipologicas de superficie y terreno. La tecnologia hiperespectral o espectrometria de imagen ofrece la posibilidad potencial de caracterizar con precision el estado de los materiales que conforman las diversas superficies en base a su respuesta espectral. Este estado suele ser variable, mientras que las observaciones se producen en un numero limitado y para determinadas condiciones de iluminacion. Al aumentar el numero de bandas espectrales aumenta tambien el numero de muestras necesarias para definir espectralmente las clases en lo que se conoce como Maldicion de la Dimensionalidad o Efecto Hughes (Bellman, 1957), muestras habitualmente no disponibles y costosas de obtener, no hay mas que pensar en lo que ello implica en la Exploracion Planetaria. Bajo la definicion de anomalia en su sentido espectral como la respuesta significativamente diferente de un pixel de imagen respecto de su entorno, el objeto central abordado en la Tesis estriba primero en como reducir la dimensionalidad de la informacion en los datos hiperespectrales, discriminando la mas significativa para la deteccion de respuestas anomalas, y segundo, en establecer la relacion entre anomalias espectrales detectadas y lo que hemos denominado anomalias informacionales, es decir, anomalias que aportan algun tipo de informacion real de las superficies o materiales que las producen. En la deteccion de respuestas anomalas se asume un no conocimiento previo de los objetivos, de tal manera que los pixeles se separan automaticamente en funcion de su informacion espectral significativamente diferenciada respecto de un fondo que se estima, bien de manera global para toda la escena, bien localmente por segmentacion de la imagen. La metodologia desarrollada se ha centrado en la implicacion de la definicion estadistica del fondo espectral, proponiendo un nuevo enfoque que permite discriminar anomalias respecto fondos segmentados en diferentes grupos de longitudes de onda del espectro, explotando la potencialidad de separacion entre el espectro electromagnetico reflectivo y emisivo. Se ha estudiado la eficiencia de los principales algoritmos de deteccion de anomalias, contrastando los resultados del algoritmo RX (Reed and Xiaoli, 1990) adoptado como estandar por la comunidad cientifica, con el metodo UTD (Uniform Targets Detector), su variante RXD-UTD, metodos basados en subespacios SSRX (Subspace RX) y metodo basados en proyecciones de subespacios de imagen, como OSPRX (Orthogonal Subspace Projection RX) y PP (Projection Pursuit). Se ha desarrollado un nuevo metodo, evaluado y contrastado por los anteriores, que supone una variacion de PP y describe el fondo espectral mediante el analisis discriminante de bandas del espectro electromagnetico, separando las anomalias con el algortimo denominado Detector de Anomalias de Fondo Termico o DAFT aplicable a sensores que registran datos en el espectro emisivo. Se han evaluado los diferentes metodos de deteccion de anomalias en rangos del espectro electromagnetico del visible e infrarrojo cercano (Visible and Near Infrared-VNIR), infrarrojo de onda corta (Short Wavelenght Infrared-SWIR), infrarrojo medio (Meadle Infrared-MIR) e infrarrojo termico (Thermal Infrared-TIR). La respuesta de las superficies en las distintas longitudes de onda del espectro electromagnetico junto con su entorno, influyen en el tipo y frecuencia de las anomalias espectrales que puedan provocar. Es por ello que se han utilizado en la investigacion cubos de datos hiperepectrales procedentes de los sensores aeroportados cuya estrategia y diseno en la construccion espectrometrica de la imagen difiere. Se han evaluado conjuntos de datos de test de los sensores AHS (Airborne Hyperspectral System), HyMAP Imaging Spectrometer, CASI (Compact Airborne Spectrographic Imager), AVIRIS (Airborne Visible Infrared Imaging Spectrometer), HYDICE (Hyperspectral Digital Imagery Collection Experiment) y MASTER (MODIS/ASTER Simulator). Se han disenado experimentos sobre ambitos naturales, urbanos y semiurbanos de diferente complejidad. Se ha evaluado el comportamiento de los diferentes detectores de anomalias a traves de 23 tests correspondientes a 15 areas de estudio agrupados en 6 espacios o escenarios: Urbano - E1, Semiurbano/Industrial/Periferia Urbana - E2, Forestal - E3, Agricola - E4, Geologico/Volcanico - E5 y Otros Espacios Agua, Nubes y Sombras - E6. El tipo de sensores evaluados se caracteriza por registrar imagenes en un amplio rango de bandas, estrechas y contiguas, del espectro electromagnetico. La Tesis se ha centrado en el desarrollo de tecnicas que permiten separar y extraer automaticamente pixeles o grupos de pixeles cuya firma espectral difiere de manera discriminante de las que tiene alrededor, adoptando para ello como espacio muestral parte o el conjunto de las bandas espectrales en las que ha registrado radiancia el sensor hiperespectral. Un factor a tener en cuenta en la investigacion ha sido el propio instrumento de medida, es decir, la caracterizacion de los distintos subsistemas, sensores imagen y auxiliares, que intervienen en el proceso. Para poder emplear cuantitativamente los datos medidos ha sido necesario definir las relaciones espaciales y espectrales del sensor con la superficie observada y las potenciales anomalias y patrones objetivos de deteccion. Se ha analizado la repercusion que en la deteccion de anomalias tiene el tipo de sensor, tanto en su configuracion espectral como en las estrategias de diseno a la hora de registrar la radiacion prodecente de las superficies, siendo los dos tipos principales de sensores estudiados los barredores o escaneres de espejo giratorio (whiskbroom) y los barredores o escaneres de empuje (pushbroom). Se han definido distintos escenarios en la investigacion, lo que ha permitido abarcar una amplia variabilidad de entornos geomorfologicos y de tipos de coberturas, en ambientes mediterraneos, de latitudes medias y tropicales. En resumen, esta Tesis presenta una tecnica de deteccion de anomalias para datos hiperespectrales denominada DAFT en su variante de PP, basada en una reduccion de la dimensionalidad proyectando el fondo en un rango de longitudes de onda del espectro termico distinto de la proyeccion de las anomalias u objetivos sin firma espectral conocida. La metodologia propuesta ha sido probada con imagenes hiperespectrales reales de diferentes sensores y en diferentes escenarios o espacios, por lo tanto de diferente fondo espectral tambien, donde los resultados muestran los beneficios de la aproximacion en la deteccion de una gran variedad de objetos cuyas firmas espectrales tienen suficiente desviacion respecto del fondo. La tecnica resulta ser automatica en el sentido de que no hay necesidad de ajuste de parametros, dando resultados significativos en todos los casos. Incluso los objetos de tamano subpixel, que no pueden distinguirse a simple vista por el ojo humano en la imagen original, pueden ser detectados como anomalias. Ademas, se realiza una comparacion entre el enfoque propuesto, la popular tecnica RX y otros detectores tanto en su modalidad global como local. El metodo propuesto supera a los demas en determinados escenarios, demostrando su capacidad para reducir la proporcion de falsas alarmas. Los resultados del algoritmo automatico DAFT desarrollado, han demostrado la mejora en la definicion cualitativa de las anomalias espectrales que identifican a entidades diferentes en o bajo superficie, reemplazando para ello el modelo clasico de distribucion normal con un metodo robusto que contempla distintas alternativas desde el momento mismo de la adquisicion del dato hiperespectral. Para su consecucion ha sido necesario analizar la relacion entre parametros biofisicos, como la reflectancia y la emisividad de los materiales, y la distribucion espacial de entidades detectadas respecto de su entorno. Por ultimo, el algoritmo DAFT ha sido elegido como el mas adecuado para sensores que adquieren datos en el TIR, ya que presenta el mejor acuerdo con los datos de referencia, demostrando una gran eficacia computacional que facilita su implementacion en un sistema de cartografia que proyecte de forma automatica en un marco geografico de referencia las anomalias detectadas, lo que confirma un significativo avance hacia un sistema en lo que se denomina cartografia en tiempo real. The aim of this Thesis is to develop a specific methodology in order to be applied in automatic detection anomalies processes using hyperspectral data also called hyperspectral scenes, and to improve the classification processes. Several scenarios, areas and their relationship with surfaces and objects have been tested. The spectral characteristics of reflectance parameter and emissivity in the pattern recognition of urban materials in several hyperspectral scenes have also been tested. Spectral ranges of the visible-near infrared (VNIR), shortwave infrared (SWIR) and thermal infrared (TIR) from hyperspectral data cubes of AHS (Airborne Hyperspectral System), HyMAP Imaging Spectrometer, CASI (Compact Airborne Spectrographic Imager), AVIRIS (Airborne Visible Infrared Imaging Spectrometer), HYDICE (Hyperspectral Digital Imagery Collection Experiment) and MASTER (MODIS/ASTER Simulator) have been used in this research. It is assumed that there is not prior knowledge of the targets in anomaly detection. Thus, the pixels are automatically separated according to their spectral information, significantly differentiated with respect to a background, either globally for the full scene, or locally by the image segmentation. Several experiments on different scenarios have been designed, analyzing the behavior of the standard RX anomaly detector and different methods based on subspace, image projection and segmentation-based anomaly detection methods. Results and their consequences in unsupervised classification processes are discussed. Detection of spectral anomalies aims at extracting automatically pixels that show significant responses in relation of their surroundings. This Thesis deals with the unsupervised technique of target detection, also called anomaly detection. Since this technique assumes no prior knowledge about the target or the statistical characteristics of the data, the only available option is to look for objects that are differentiated from the background. Several methods have been developed in the last decades, allowing a better understanding of the relationships between the image dimensionality and the optimization of search procedures as well as the subpixel differentiation of the spectral mixture and its implications in anomalous responses. In other sense, image spectrometry has proven to be efficient in the characterization of materials, based on statistical methods using a specific reflection and absorption bands. Spectral configurations in the VNIR, SWIR and TIR have been successfully used for mapping materials in different urban scenarios. There has been an increasing interest in the use of high resolution data (both spatial and spectral) to detect small objects and to discriminate surfaces in areas with urban complexity. This has come to be known as target detection which can be either supervised or unsupervised. In supervised target detection, algorithms lean on prior knowledge, such as the spectral signature. The detection process for matching signatures is not straightforward due to the complications of converting data airborne sensor with material spectra in the ground. This could be further complicated by the large number of possible objects of interest, as well as uncertainty as to the reflectance or emissivity of these objects and surfaces. An important objective in this research is to establish relationships that allow linking spectral anomalies with what can be called informational anomalies and, therefore, identify information related to anomalous responses in some places rather than simply spotting differences from the background. The development in recent years of new hyperspectral sensors and techniques, widen the possibilities for applications in remote sensing of the Earth. Remote sensing systems measure and record electromagnetic disturbances that the surveyed objects induce in their surroundings, by means of different sensors mounted on airborne or space platforms. Map updating is important for management and decisions making people, because of the fast changes that usually happen in natural, urban and semi urban areas. It is necessary to optimize the methodology for obtaining the best from remote sensing techniques from hyperspectral data. The first problem with hyperspectral data is to reduce the dimensionality, keeping the maximum amount of information. Hyperspectral sensors augment considerably the amount of information, this allows us to obtain a better precision on the separation of material but at the same time it is necessary to calculate a bigger number of parameters, and the precision lowers with the increase in the number of bands. This is known as the Hughes effects (Bellman, 1957) . Hyperspectral imagery allows us to discriminate between a huge number of different materials however some land and urban covers are made up with similar material and respond similarly which produces confusion in the classification. The training and the algorithm used for mapping are also important for the final result and some properties of thermal spectrum for detecting land cover will be studied. In summary, this Thesis presents a new technique for anomaly detection in hyperspectral data called DAFT, as a PP's variant, based on dimensionality reduction by projecting anomalies or targets with unknown spectral signature to the background, in a range thermal spectrum wavelengths. The proposed methodology has been tested with hyperspectral images from different imaging spectrometers corresponding to several places or scenarios, therefore with different spectral background. The results show the benefits of the approach to the detection of a variety of targets whose spectral signatures have sufficient deviation in relation to the background. DAFT is an automated technique in the sense that there is not necessary to adjust parameters, providing significant results in all cases. Subpixel anomalies which cannot be distinguished by the human eye, on the original image, however can be detected as outliers due to the projection of the VNIR end members with a very strong thermal contrast. Furthermore, a comparison between the proposed approach and the well-known RX detector is performed at both modes, global and local. The proposed method outperforms the existents in particular scenarios, demonstrating its performance to reduce the probability of false alarms. The results of the automatic algorithm DAFT have demonstrated improvement in the qualitative definition of the spectral anomalies by replacing the classical model by the normal distribution with a robust method. For their achievement has been necessary to analyze the relationship between biophysical parameters such as reflectance and emissivity, and the spatial distribution of detected entities with respect to their environment, as for example some buried or semi-buried materials, or building covers of asbestos, cellular polycarbonate-PVC or metal composites. Finally, the DAFT method has been chosen as the most suitable for anomaly detection using imaging spectrometers that acquire them in the thermal infrared spectrum, since it presents the best results in comparison with the reference data, demonstrating great computational efficiency that facilitates its implementation in a mapping system towards, what is called, Real-Time Mapping.