57 research outputs found

    Automatic Chinese Postal Address Block Location Using Proximity Descriptors and Cooperative Profit Random Forests.

    Get PDF
    Locating the destination address block is key to automated sorting of mails. Due to the characteristics of Chinese envelopes used in mainland China, we here exploit proximity cues in order to describe the investigated regions on envelopes. We propose two proximity descriptors encoding spatial distributions of the connected components obtained from the binary envelope images. To locate the destination address block, these descriptors are used together with cooperative profit random forests (CPRFs). Experimental results show that the proposed proximity descriptors are superior to two component descriptors, which only exploit the shape characteristics of the individual components, and the CPRF classifier produces higher recall values than seven state-of-the-art classifiers. These promising results are due to the fact that the proposed descriptors encode the proximity characteristics of the binary envelope images, and the CPRF classifier uses an effective tree node split approach

    Image analysis for the study of chromatin distribution in cell nuclei with application to cervical cancer screening

    Get PDF

    Classifiers and machine learning techniques for image processing and computer vision

    Get PDF
    Orientador: Siome Klein GoldensteinTese (doutorado) - Universidade Estadual de Campinas, Instituto da ComputaçãoResumo: Neste trabalho de doutorado, propomos a utilizaçãoo de classificadores e técnicas de aprendizado de maquina para extrair informações relevantes de um conjunto de dados (e.g., imagens) para solução de alguns problemas em Processamento de Imagens e Visão Computacional. Os problemas de nosso interesse são: categorização de imagens em duas ou mais classes, detecçãao de mensagens escondidas, distinção entre imagens digitalmente adulteradas e imagens naturais, autenticação, multi-classificação, entre outros. Inicialmente, apresentamos uma revisão comparativa e crítica do estado da arte em análise forense de imagens e detecção de mensagens escondidas em imagens. Nosso objetivo é mostrar as potencialidades das técnicas existentes e, mais importante, apontar suas limitações. Com esse estudo, mostramos que boa parte dos problemas nessa área apontam para dois pontos em comum: a seleção de características e as técnicas de aprendizado a serem utilizadas. Nesse estudo, também discutimos questões legais associadas a análise forense de imagens como, por exemplo, o uso de fotografias digitais por criminosos. Em seguida, introduzimos uma técnica para análise forense de imagens testada no contexto de detecção de mensagens escondidas e de classificação geral de imagens em categorias como indoors, outdoors, geradas em computador e obras de arte. Ao estudarmos esse problema de multi-classificação, surgem algumas questões: como resolver um problema multi-classe de modo a poder combinar, por exemplo, caracteríisticas de classificação de imagens baseadas em cor, textura, forma e silhueta, sem nos preocuparmos demasiadamente em como normalizar o vetor-comum de caracteristicas gerado? Como utilizar diversos classificadores diferentes, cada um, especializado e melhor configurado para um conjunto de caracteristicas ou classes em confusão? Nesse sentido, apresentamos, uma tecnica para fusão de classificadores e caracteristicas no cenário multi-classe através da combinação de classificadores binários. Nós validamos nossa abordagem numa aplicação real para classificação automática de frutas e legumes. Finalmente, nos deparamos com mais um problema interessante: como tornar a utilização de poderosos classificadores binarios no contexto multi-classe mais eficiente e eficaz? Assim, introduzimos uma tecnica para combinação de classificadores binarios (chamados classificadores base) para a resolução de problemas no contexto geral de multi-classificação.Abstract: In this work, we propose the use of classifiers and machine learning techniques to extract useful information from data sets (e.g., images) to solve important problems in Image Processing and Computer Vision. We are particularly interested in: two and multi-class image categorization, hidden messages detection, discrimination among natural and forged images, authentication, and multiclassification. To start with, we present a comparative survey of the state-of-the-art in digital image forensics as well as hidden messages detection. Our objective is to show the importance of the existing solutions and discuss their limitations. In this study, we show that most of these techniques strive to solve two common problems in Machine Learning: the feature selection and the classification techniques to be used. Furthermore, we discuss the legal and ethical aspects of image forensics analysis, such as, the use of digital images by criminals. We introduce a technique for image forensics analysis in the context of hidden messages detection and image classification in categories such as indoors, outdoors, computer generated, and art works. From this multi-class classification, we found some important questions: how to solve a multi-class problem in order to combine, for instance, several different features such as color, texture, shape, and silhouette without worrying about the pre-processing and normalization of the combined feature vector? How to take advantage of different classifiers, each one custom tailored to a specific set of classes in confusion? To cope with most of these problems, we present a feature and classifier fusion technique based on combinations of binary classifiers. We validate our solution with a real application for automatic produce classification. Finally, we address another interesting problem: how to combine powerful binary classifiers in the multi-class scenario more effectively? How to boost their efficiency? In this context, we present a solution that boosts the efficiency and effectiveness of multi-class from binary techniques.DoutoradoEngenharia de ComputaçãoDoutor em Ciência da Computaçã

    Document image processing using irregular pyramid structure

    Get PDF
    Ph.DDOCTOR OF PHILOSOPH

    Methodology for high resolution spatial analysis of the physical flood susceptibility of buildings in large river floodplains

    Get PDF
    The impacts of floods on buildings in urban areas are increasing due to the intensification of extreme weather events, unplanned or uncontrolled settlements and the rising vulnerability of assets. There are some approaches available for assessing the flood damage to buildings and critical infrastructure. To this point, however, it is extremely difficult to adapt these methods widely, due to the lack of high resolution classification and characterisation approaches for built structures. To overcome this obstacle, this work presents: first, a conceptual framework for understanding the physical flood vulnerability and the physical flood susceptibility of buildings, second, a methodological framework for the combination of methods and tools for a large-scale and high-resolution analysis and third, the testing of the methodology in three pilot sites with different development conditions. The conceptual framework narrows down an understanding of flood vulnerability, physical flood vulnerability and physical flood susceptibility and its relation to social and economic vulnerabilities. It describes the key features causing the physical flood susceptibility of buildings as a component of the vulnerability. The methodological framework comprises three modules: (i) methods for setting up a building topology, (ii) methods for assessing the susceptibility of representative buildings of each building type and (iii) the integration of the two modules with technological tools. The first module on the building typology is based on a classification of remote sensing data and GIS analysis involving seven building parameters, which appeared to be relevant for a classification of buildings regarding potential flood impacts. The outcome is a building taxonomic approach. A subsequent identification of representative buildings is based on statistical analyses and membership functions. The second module on the building susceptibility for representative buildings bears on the derivation of depth-physical impact functions. It relates the principal building components, including their heights, dimensions and materials, to the damage from different water levels. The material’s susceptibility is estimated based on international studies on the resistance of building materials and a fuzzy expert analysis. Then depth-physical impact functions are calculated referring to the principal components of the buildings which can be affected by different water levels. Hereby, depth-physical impact functions are seen as a means for the interrelation between the water level and the physical impacts. The third module provides the tools for implementing the methodology. This tool compresses the architecture for feeding the required data on the buildings with their relations to the building typology and the building-type specific depth-physical impact function supporting the automatic process. The methodology is tested in three flood plains pilot sites: (i) in the settlement of the Barrio Sur in Magangué and (ii) in the settlement of La Peña in Cicuco located on the flood plain of Magdalena River, Colombia and (iii) in a settlement of the city of Dresden, located on the Elbe River, Germany. The testing of the methodology covers the description of data availability and accuracy, the steps for deriving the depth-physical impact functions of representative buildings and the final display of the spatial distribution of the physical flood susceptibility. The discussion analyses what are the contributions of this work evaluating the findings of the methodology’s testing with the dissertation goals. The conclusions of the work show the contributions and limitations of the research in terms of methodological and empirical advancements and the general applicability in flood risk management.:1 INTRODUCTION 1 1.1 Background 1 1.2 State of the art 2 1.3 Problem statement 6 1.4 Objectives 6 1.5 Approach and outline 6 2 CONCEPTUAL FRAMEWORK 9 2.1 Flood vulnerability 10 2.2 Physical flood vulnerability 12 2.3 Physical flood susceptibility 14 3 METHODOLOGICAL FRAMEWORK 23 3.1 Module 1: Building taxonomy for settlements 24 3.1.1 Extraction of building features 24 3.1.2 Derivation of building parameters for setting up a building taxonomy 38 3.1.3 Selection of representative buildings for a building susceptibility assessment 51 3.2 Module 2: Physical susceptibility of representative buildings 57 3.2.1 Identification of building components 57 3.2.2 Qualification of building material susceptibility 62 3.2.3 Derivation of a depth-physical impact function 71 3.3 Module 3: Technological integration 77 3.3.1 Combination of the depth-physical impact function with the building taxonomic code 77 3.3.2 Tools supporting the physical susceptibility analysis 78 3.3.3 The users and their requirements 79 4 RESULTS OF THE METHODOLOGY TESTING 83 4.1 Pilot site “Kleinzschachwitz” – Dresden, Germany – Elbe River 83 4.1.1 Module 1: Building taxonomy – “Kleinzschachwitz” 85 4.1.2 Module 2: Physical susceptibility of representative buildings – “Kleinzschachwitz” 97 4.1.3 Module 3: Technological integration – “Kleinzschachwitz” 103 4.2 Pilot site “La Peña” – Cicuco, Colombia – Magdalena River 107 4.2.1 Module 1: Building taxonomy – “La Peña” 108 4.2.2 Module 2: Physical susceptibility of representative buildings – “La Peña” 121 4.2.3 Module 3: Technological integration– “La Peña” 129 4.3 Pilot site “Barrio Sur” – Magangué, Colombia – Magdalena River 133 4.3.1 Module 1: Building taxonomy – “Barrio Sur” 133 4.3.2 Module 2: Physical susceptibility of representative buildings – “Barrio Sur” 141 4.3.3 Module 3: Technological integration – “Barrio Sur” 147 4.4 Empirical findings 151 4.4.1 Empirical findings of Module 1 151 4.4.2 Empirical findings of Module 2 155 4.4.3 Empirical findings of Module 3 157 4.4.4 Guidance of the methodology 157 5 DISCUSSION 161 5.1 Discussion on the conceptual framework 161 5.2 Discussion on the methodological framework 161 5.2.1 Discussion on Module 1: the building taxonomic approach 162 5.2.2 Discussion on Module 2: the depth-physical impact function 164 6 CONCLUSIONS AND OUTLOOK 167 6.1 Conclusions 167 6.2 Outlook 168 REFERENCES 171 INDEX OF FIGURES 199 INDEX OF TABLES 201 APPENDICES 203In vielen Städten nehmen die Auswirkungen von Hochwasser auf Gebäude aufgrund immer extremerer Wetterereignisse, unkontrollierbarer Siedlungsbauten und der steigenden Vulnerabilität von Besitztümern stetig zu. Es existieren zwar bereits Ansätze zur Beurteilung von Wasserschäden an Gebäuden und Infrastrukturknotenpunkten. Doch ist es bisher schwierig, diese Methoden großräumig anzuwenden, da es an einer präzisen Klassifizierung und Charakterisierung von Gebäuden und anderen baulichen Anlagen fehlt. Zu diesem Zweck sollen in dieser Arbeit erstens ein Konzept für ein genaueres Verständnis der physischen Vulnerabilität von Gebäuden gegenüber Hochwasser dargelegt, zweitens ein methodisches Verfahren zur Kombination der bestehenden Methoden und Hilfsmittel mit dem Ziel einer großräumigen und hochauflösenden Analyse erarbeitet und drittens diese Methode an drei Pilotstandorten mit unterschiedlichem Ausbauzustand erprobt werden. Die Rahmenbedingungen des Konzepts grenzen die Begriffe der Vulnerabilität, der physischen Vulnerabilität und der physischen Anfälligkeit gegenüber Hochwasser ein und erörtern deren Beziehung zur sozialen und ökonomischen Vulnerabilität. Es werden die Merkmale der physischen Anfälligkeit von Gebäuden gegenüber Hochwasser als Bestandteil der Vulnerabilität definiert. Das methodische Verfahren umfasst drei Module: (i) Methoden zur Erstellung einer Gebäudetypologie, (ii) Methoden zur Bewertung der Anfälligkeit repräsentativer Gebäude jedes Gebäudetyps und (iii) die Kombination der beiden Module mit Hilfe technologischer Hilfsmittel. Das erste Modul zur Gebäudetypologie basiert auf der Klassifizierung von Fernerkundungsdaten und GIS-Analysen anhand von sieben Gebäudeparametern, die sich für die Klassifizierung von Gebäuden bezüglich ihres Risikopotenzials bei Hochwasser als wichtig erweisen. Daraus ergibt sich ein Ansatz zur Gebäudeklassifizierung. Die anschließende Ermittlung repräsentativer Gebäude beruht auf statistischen Analysen und Zugehörigkeitsfunktionen. Das zweite Modul zur Anfälligkeit repräsentativer Gebäude beruht auf der Ableitung von Funktion von Wasserstand und physischer Einwirkung. Es setzt die relevanten Gebäudemerkmale, darunter Höhe, Maße und Materialien, in Beziehung zum erwartbaren Schaden bei unterschiedlichen Wasserständen. Die Materialanfälligkeit wird aufgrund internationaler Studien zur Festigkeit von Baustoffen sowie durch Anwendung eines Fuzzy-Logic-Expertensystems eingeschätzt. Anschließend werden Wasserstand-Schaden-Funktionen unter Einbeziehung der Hauptgebäudekomponenten berechnet, die durch unterschiedliche Wasserstände in Mitleidenschaft gezogen werden können. Funktion von Wasserstand und physischer Einwirkung dienen hier dazu, den jeweiligen Wasserstand und die physischen Auswirkung in Beziehung zueinander zu setzen. Das dritte Modul stellt die zur Umsetzung der Methoden notwendigen Hilfsmittel vor. Zur Unterstützung des automatisierten Verfahrens dienen Hilfsmittel, die die Gebäudetypologie mit der Funktion von Wasserstand und physischer Einwirkung für Gebäude in Hochwassergebieten kombinieren. Die Methoden wurden anschließend in drei hochwassergefährdeten Pilotstandorten getestet: (i) in den Siedlungsgebieten von Barrio Sur in Magangué und (ii) von La Pena in Cicuco, zwei Überschwemmungsgebiete des Magdalenas in Kolumbien, und (iii) im Stadtgebiet von Dresden, das an der Elbe liegt. Das Testverfahren umfasst die Beschreibung der Datenverfügbarkeit und genauigkeit, die einzelnen Schritte zur Analyse der. Funktion von Wasserstand und physischer Einwirkung repräsentativer Gebäude sowie die Darstellung der räumlichen Verteilung der physischen Anfälligkeit für Hochwasser. In der Diskussion wird der Beitrag dieser Arbeit zur Beurteilung der Erkenntnisse der getesteten Methoden anhand der Ziele dieser Dissertation analysiert. Die Folgerungen beleuchten abschließend die Fortschritte und auch Grenzen der Forschung hinsichtlich methodischer und empirischer Entwicklungen sowie deren allgemeine Anwendbarkeit im Bereich des Hochwasserschutzes.:1 INTRODUCTION 1 1.1 Background 1 1.2 State of the art 2 1.3 Problem statement 6 1.4 Objectives 6 1.5 Approach and outline 6 2 CONCEPTUAL FRAMEWORK 9 2.1 Flood vulnerability 10 2.2 Physical flood vulnerability 12 2.3 Physical flood susceptibility 14 3 METHODOLOGICAL FRAMEWORK 23 3.1 Module 1: Building taxonomy for settlements 24 3.1.1 Extraction of building features 24 3.1.2 Derivation of building parameters for setting up a building taxonomy 38 3.1.3 Selection of representative buildings for a building susceptibility assessment 51 3.2 Module 2: Physical susceptibility of representative buildings 57 3.2.1 Identification of building components 57 3.2.2 Qualification of building material susceptibility 62 3.2.3 Derivation of a depth-physical impact function 71 3.3 Module 3: Technological integration 77 3.3.1 Combination of the depth-physical impact function with the building taxonomic code 77 3.3.2 Tools supporting the physical susceptibility analysis 78 3.3.3 The users and their requirements 79 4 RESULTS OF THE METHODOLOGY TESTING 83 4.1 Pilot site “Kleinzschachwitz” – Dresden, Germany – Elbe River 83 4.1.1 Module 1: Building taxonomy – “Kleinzschachwitz” 85 4.1.2 Module 2: Physical susceptibility of representative buildings – “Kleinzschachwitz” 97 4.1.3 Module 3: Technological integration – “Kleinzschachwitz” 103 4.2 Pilot site “La Peña” – Cicuco, Colombia – Magdalena River 107 4.2.1 Module 1: Building taxonomy – “La Peña” 108 4.2.2 Module 2: Physical susceptibility of representative buildings – “La Peña” 121 4.2.3 Module 3: Technological integration– “La Peña” 129 4.3 Pilot site “Barrio Sur” – Magangué, Colombia – Magdalena River 133 4.3.1 Module 1: Building taxonomy – “Barrio Sur” 133 4.3.2 Module 2: Physical susceptibility of representative buildings – “Barrio Sur” 141 4.3.3 Module 3: Technological integration – “Barrio Sur” 147 4.4 Empirical findings 151 4.4.1 Empirical findings of Module 1 151 4.4.2 Empirical findings of Module 2 155 4.4.3 Empirical findings of Module 3 157 4.4.4 Guidance of the methodology 157 5 DISCUSSION 161 5.1 Discussion on the conceptual framework 161 5.2 Discussion on the methodological framework 161 5.2.1 Discussion on Module 1: the building taxonomic approach 162 5.2.2 Discussion on Module 2: the depth-physical impact function 164 6 CONCLUSIONS AND OUTLOOK 167 6.1 Conclusions 167 6.2 Outlook 168 REFERENCES 171 INDEX OF FIGURES 199 INDEX OF TABLES 201 APPENDICES 203El impacto de las inundaciones sobre los edificios en zonas urbanas es cada vez mayor debido a la intensificación de los fenómenos meteorológicos extremos, asentamientos no controlados o no planificados y su creciente vulnerabilidad. Hay métodos disponibles para evaluar los daños por inundación en edificios e infraestructuras críticas. Sin embargo, es muy difícil implementar estos métodos sistemáticamente en grandes áreas debido a la falta de clasificación y caracterización de estructuras construidas en resoluciones detalladas. Para superar este obstáculo, este trabajo se enfoca, en primer lugar, en desarrollar un marco conceptual para comprender la vulnerabilidad y susceptibilidad física de edificios por inudaciones, en segundo lugar, en desarrollar un marco metodológico para la combinación de los métodos y herramientas para una análisis de alta resolución y en tercer lugar, la prueba de la metodología en tres sitios experimentales, con distintas condiciones de desarrollo. El marco conceptual se enfoca en comprender la vulnerabilidad y susceptibility de las edificaciones frente a inundaciones, y su relación con la vulnerabilidad social y económica. En él se describen las principales características físicas de la susceptibilidad de edificicaiones como un componente de la vulnerabilidad. El marco metodológico consta de tres módulos: (i) métodos para la derivación de topología de construcciones, (ii) métodos para evaluar la susceptibilidad de edificios representativos y (iii) la integración de los dos módulos a través herramientas tecnológicas. El primer módulo de topología de construcciones se basa en una clasificación de datos de sensoramiento rémoto y procesamiento SIG para la extracción de siete parámetros de las edficaciones. Este módulo parece ser aplicable para una clasificación de los edificios en relación con los posibles impactos de las inundaciones. El resultado es una taxonomía de las edificaciones y una posterior identificación de edificios representativos que se basa en análisis estadísticos y funciones de pertenencia. El segundo módulo consiste en el análisis de susceptibilidad de las construcciones representativas a través de funciones de profundidad del impacto físico. Las cuales relacionan los principales componentes de la construcción, incluyendo sus alturas, dimensiones y materiales con los impactos físicos a diferentes niveles de agua. La susceptibilidad del material se calcula con base a estudios internacionales sobre la resistencia de los materiales y un análisis a través de sistemas expertos difusos. Aquí, las funciones de profundidad de impacto físico son considerados como un medio para la interrelación entre el nivel del agua y los impactos físicos. El tercer módulo proporciona las herramientas necesarias para la aplicación de la metodología. Estas herramientas tecnológicas consisten en la arquitectura para la alimentación de los datos relacionados a la tipología de construcciones con las funciones de profundidad del impacto físico apoyado en procesos automáticos. La metodología es probada en tres sitios piloto: (i) en el Barrio Sur en Magangué y (ii) en la barrio de La Peña en Cicuco situado en la llanura inundable del Río Magdalena, Colombia y (iii) en barrio Kleinzschachwitz de la ciudad de Dresden, situado a orillas del río Elba, en Alemania. Las pruebas de la metodología abarca la descripción de la disponibilidad de los datos y la precisión, los pasos a seguir para obtener las funciones profundidad de impacto físico de edificios representativos y la presentación final de la distribución espacial de la susceptibilidad física frente inundaciones El discusión analiza las aportaciones de este trabajo y evalua los resultados de la metodología con relación a los objetivos. Las conclusiones del trabajo, muestran los aportes y limitaciones de la investigación en términos de avances metodológicos y empíricos y la aplicabilidad general de gestión del riesgo de inundaciones.:1 INTRODUCTION 1 1.1 Background 1 1.2 State of the art 2 1.3 Problem statement 6 1.4 Objectives 6 1.5 Approach and outline 6 2 CONCEPTUAL FRAMEWORK 9 2.1 Flood vulnerability 10 2.2 Physical flood vulnerability 12 2.3 Physical flood susceptibility 14 3 METHODOLOGICAL FRAMEWORK 23 3.1 Module 1: Building taxonomy for settlements 24 3.1.1 Extraction of building features 24 3.1.2 Derivation of building parameters for setting up a building taxonomy 38 3.1.3 Selection of representative buildings for a building susceptibility assessment 51 3.2 Module 2: Physical susceptibility of representative buildings 57 3.2.1 Identification of building components 57 3.2.2 Qualification of building material susceptibility 62 3.2.3 Derivation of a depth-physical impact function 71 3.3 Module 3: Technological integration 77 3.3.1 Combination of the depth-physical impact function with the building taxonomic code 77 3.3.2 Tools supporting the physical susceptibility analysis 78 3.3.3 The users and their requirements 79 4 RESULTS OF THE METHODOLOGY TESTING 83 4.1 Pilot site “Kleinzschachwitz” – Dresden, Germany – Elbe River 83 4.1.1 Module 1: Building taxonomy – “Kleinzschachwitz” 85 4.1.2 Module 2: Physical susceptibility of representative buildings – “Kleinzschachwitz” 97 4.1.3 Module 3: Technological integration – “Kleinzschachwitz” 103 4.2 Pilot site “La Peña” – Cicuco, Colombia – Magdalena River 107 4.2.1 Module 1: Building taxonomy – “La Peña” 108 4.2.2 Module 2: Physical susceptibility of representative buildings – “La Peña” 121 4.2.3 Module 3: Technological integration– “La Peña” 129 4.3 Pilot site “Barrio Sur” – Magangué, Colombia – Magdalena River 133 4.3.1 Module 1: Building taxonomy – “Barrio Sur” 133 4.3.2 Module 2: Physical susceptibility of representative buildings – “Barrio Sur” 141 4.3.3 Module 3: Technological integration – “Barrio Sur” 147 4.4 Empirical findings 151 4.4.1 Empirical findings of Module 1 151 4.4.2 Empirical findings of Module 2 155 4.4.3 Empirical findings of Module 3 157 4.4.4 Guidance of the methodology 157 5 DISCUSSION 161 5.1 Discussion on the conceptual framework 161 5.2 Discussion on the methodological framework 161 5.2.1 Discussion on Module 1: the building taxonomic approach 162 5.2.2 Discussion on Module 2: the depth-physical impact function 164 6 CONCLUSIONS AND OUTLOOK 167 6.1 Conclusions 167 6.2 Outlook 168 REFERENCES 171 INDEX OF FIGURES 199 INDEX OF TABLES 201 APPENDICES 20

    Statistical and image analysis methods and applications

    Get PDF

    OGRS2012 Symposium Proceedings

    Get PDF
    Do you remember the Open Source Geospatial Research and Education Symposium (OGRS) in Nantes? "Les Machines de l’Île", the Big Elephant, the "Storm Boat" with Claramunt, Petit et al. (2009), and "le Biniou et la Bombarde"? A second edition of OGRS was promised, and that promise is now fulfilled in OGRS 2012, Yverdon-les-Bains, Switzerland, October 24-26, 2012. OGRS is a meeting dedicated to sharing knowledge, new solutions, methods, practices, ideas and trends in the field of geospatial information through the development and the use of free and open source software in both research and education. In recent years, the development of geospatial free and open source software (GFOSS) has breathed new life into the geospatial domain. GFOSS has been extensively promoted by FOSS4G events, which evolved from meetings which gathered together interested GFOSS development communities to a standard business conference. More in line with the academic side of the FOSS4G conferences, OGRS is a rather neutral forum whose goal is to assemble a community whose main concern is to find new solutions by sharing knowledge and methods free of software license limits. This is why OGRS is primarily concerned with the academic world, though it also involves public institutions, organizations and companies interested in geospatial innovation. This symposium is therefore not an exhibition for presenting existing industrial software solutions, but an event we hope will act as a catalyst for research and innovation and new collaborations between research teams, public agencies and industries. An educational aspect has recently been added to the content of the symposium. This important addition examines the knowledge triangle - research, education, and innovation - through the lens of how open source methods can improve education efficiency. Based on their experience, OGRS contributors bring to the table ideas on how open source training is likely to offer pedagogical advantages to equip students with the skills and knowledge necessary to succeed in tomorrow’s geospatial labor market. OGRS brings together a large collection of current innovative research projects from around the world, with the goal of examining how research uses and contributes to open source initiatives. By presenting their research, OGRS contributors shed light on how the open-source approach impacts research, and vice-versa. The organizers of the symposium wish to demonstrate how the use and development of open source software strengthen education, research and innovation in geospatial fields. To support this approach, the present proceedings propose thirty short papers grouped under the following thematic headings: Education, Earth Science & Landscape, Data, Remote Sensing, Spatial Analysis, Urban Simulation and Tools. These papers are preceded by the contributions of the four keynote speakers: Prof Helena Mitasova, Dr Gérard Hégron, Prof Sergio Rey and Prof Robert Weibel, who share their expertise in research and education in order to highlight the decisive advantages of openness over the limits imposed by the closed-source license system

    Geomorphometry 2020. Conference Proceedings

    Get PDF
    Geomorphometry is the science of quantitative land surface analysis. It gathers various mathematical, statistical and image processing techniques to quantify morphological, hydrological, ecological and other aspects of a land surface. Common synonyms for geomorphometry are geomorphological analysis, terrain morphometry or terrain analysis and land surface analysis. The typical input to geomorphometric analysis is a square-grid representation of the land surface: a digital elevation (or land surface) model. The first Geomorphometry conference dates back to 2009 and it took place in Zürich, Switzerland. Subsequent events were in Redlands (California), Nánjīng (China), Poznan (Poland) and Boulder (Colorado), at about two years intervals. The International Society for Geomorphometry (ISG) and the Organizing Committee scheduled the sixth Geomorphometry conference in Perugia, Italy, June 2020. Worldwide safety measures dictated the event could not be held in presence, and we excluded the possibility to hold the conference remotely. Thus, we postponed the event by one year - it will be organized in June 2021, in Perugia, hosted by the Research Institute for Geo-Hydrological Protection of the Italian National Research Council (CNR IRPI) and the Department of Physics and Geology of the University of Perugia. One of the reasons why we postponed the conference, instead of canceling, was the encouraging number of submitted abstracts. Abstracts are actually short papers consisting of four pages, including figures and references, and they were peer-reviewed by the Scientific Committee of the conference. This book is a collection of the contributions revised by the authors after peer review. We grouped them in seven classes, as follows: • Data and methods (13 abstracts) • Geoheritage (6 abstracts) • Glacial processes (4 abstracts) • LIDAR and high resolution data (8 abstracts) • Morphotectonics (8 abstracts) • Natural hazards (12 abstracts) • Soil erosion and fluvial processes (16 abstracts) The 67 abstracts represent 80% of the initial contributions. The remaining ones were either not accepted after peer review or withdrawn by their Authors. Most of the contributions contain original material, and an extended version of a subset of them will be included in a special issue of a regular journal publication

    A Methodology to Develop Computer Vision Systems in Civil Engineering: Applications in Material Testing and Fish Tracking

    Get PDF
    [Resumen] La Visión Artificial proporciona una nueva y prometedora aproximación al campo de la Ingeniería Civil, donde es extremadamente importante medir con precisión diferentes procesos. Sin embargo, la Visión Artificial es un campo muy amplio que abarca multitud de técnicas y objetivos, y definir una aproximación de desarrollo sistemática es problemático. En esta tesis se propone una nueva metodología para desarrollar estos sistemas considerando las características y requisitos de la Ingeniería Civil. Siguiendo esta metodología se han desarrollado dos sistemas: Un sistema para la medición de desplazamientos y deformaciones en imágenes de ensayos de resistencia de materiales. Solucionando las limitaciones de los actuales sensores físicos que interfieren con el ensayo y solo proporcionan mediciones en un punto y una dirección determinada. Un sistema para la medición de la trayectoria de peces en escalas de hendidura vertical, con el que se pretende solucionar las carencias en el diseño de escalas obteniendo información sobre el comportamiento de los peces. Estas aplicaciones representan contribuciones significativas en el área, y demuestran que la metodología definida e implementada proporciona un marco de trabajo sistemático y confiable para el desarrollo de sistemas de Visión Artificial en Ingeniería Civil.[Resumo] A Visión Artificial proporciona unha nova e prometedora aproximación ó campo da Enxeñería Civil, onde é extremadamente importante medir con precisión diferentes procesos. Sen embargo, a Visión Artificial é un campo moi amplo que abarca multitude de técnicas e obxectivos, e definir unha aproximación de desenvolvemento sistemática é problemático. En esta tese proponse unha nova metodoloxía para desenvolver estes sistemas considerando as características e requisitos da Enxeñería Civil. Seguindo esta metodoloxía desenvolvéronse dous sistemas: Un sistema para a medición de desprazamentos e deformacións en imaxes de ensaios de resistencia de materiais. Solucionando as limitacións dos actuais sensores físicos que interfiren co ensaio e só proporcionan medicións nun punto e nunha dirección determinada. Un sistema para a medición da traxectoria de peixes en escalas de fenda vertical, co que se pretende solucionar as carencias no deseño de escalas obtendo información sobre o comportamento dos peixes. Estas aplicacións representan contribucións significativas na área, e demostran que a metodoloxía definida e implementada proporciona un marco de traballo sistemático e confiable para o desenvolvemento de sistemas de Visión Artificial en Enxeñería Civil.[Abstract] Computer Vision provides a new and promising approach to Civil Engineering, where it is extremely important to measure with accuracy real world processes. However, Computer Vision is a broad field, involving several techniques and topics, and the task of defining a systematic development approach is problematic. In this thesis a new methodology is carried out to develop these systems attending to the special characteristics and requirements of Civil Engineering. Following this methodology, two systems were developed: A system to measure displacements from real images of material surfaces taken during strength tests. This technique solves the limitation of current physical sensors, which interfere with the assay and which are limited to obtaining measurements in a single point of the material and in a single direction of the movement. A system to measure the trajectory of fishes in vertical slot fishways, whose purpose is to solve current lacks in the design of fishways by providing information of fish behavior. These applications represent significant contributions to the field and show that the defined and implemented methodology provides a systematic and reliable framework to develop a Computer Vision system in Civil Engineering

    Applied Metaheuristic Computing

    Get PDF
    For decades, Applied Metaheuristic Computing (AMC) has been a prevailing optimization technique for tackling perplexing engineering and business problems, such as scheduling, routing, ordering, bin packing, assignment, facility layout planning, among others. This is partly because the classic exact methods are constrained with prior assumptions, and partly due to the heuristics being problem-dependent and lacking generalization. AMC, on the contrary, guides the course of low-level heuristics to search beyond the local optimality, which impairs the capability of traditional computation methods. This topic series has collected quality papers proposing cutting-edge methodology and innovative applications which drive the advances of AMC
    corecore