182 research outputs found

    Stabilization and Imaging of Cohesionless Soil Specimens

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    abstract: This dissertation describes development of a procedure for obtaining high quality, optical grade sand coupons from frozen sand specimens of Ottawa 20/30 sand for image processing and analysis to quantify soil structure along with a methodology for quantifying the microstructure from the images. A technique for thawing and stabilizing frozen core samples was developed using optical grade Buehler® Epo-Tek® epoxy resin, a modified triaxial cell, a vacuum/reservoir chamber, a desiccator, and a moisture gauge. The uniform epoxy resin impregnation required proper drying of the soil specimen, application of appropriate confining pressure and vacuum levels, and epoxy mixing, de-airing and curing. The resulting stabilized sand specimen was sectioned into 10 mm thick coupons that were planed, ground, and polished with progressively finer diamond abrasive grit levels using the modified Allied HTP Inc. polishing method so that the soil structure could be accurately quantified using images obtained with the use of an optical microscopy technique. Illumination via Bright Field Microscopy was used to capture the images for subsequent image processing and sand microstructure analysis. The quality of resulting images and the validity of the subsequent image morphology analysis hinged largely on employment of a polishing and grinding technique that resulted in a flat, scratch free, reflective coupon surface characterized by minimal microstructure relief and good contrast between the sand particles and the surrounding epoxy resin. Subsequent image processing involved conversion of the color images first to gray scale images and then to binary images with the use of contrast and image adjustments, removal of noise and image artifacts, image filtering, and image segmentation. Mathematical morphology algorithms were used on the resulting binary images to further enhance image quality. The binary images were then used to calculate soil structure parameters that included particle roundness and sphericity, particle orientation variability represented by rose diagrams, statistics on the local void ratio variability as a function of the sample size, and the local void ratio distribution histograms using Oda's method and Voronoi tessellation method, including the skewness, kurtosis, and entropy of a gamma cumulative probability distribution fit to the local void ratio distribution.Dissertation/ThesisM.S. Civil Engineering 201

    A Methodology for Extracting Human Bodies from Still Images

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    Monitoring and surveillance of humans is one of the most prominent applications of today and it is expected to be part of many future aspects of our life, for safety reasons, assisted living and many others. Many efforts have been made towards automatic and robust solutions, but the general problem is very challenging and remains still open. In this PhD dissertation we examine the problem from many perspectives. First, we study the performance of a hardware architecture designed for large-scale surveillance systems. Then, we focus on the general problem of human activity recognition, present an extensive survey of methodologies that deal with this subject and propose a maturity metric to evaluate them. One of the numerous and most popular algorithms for image processing found in the field is image segmentation and we propose a blind metric to evaluate their results regarding the activity at local regions. Finally, we propose a fully automatic system for segmenting and extracting human bodies from challenging single images, which is the main contribution of the dissertation. Our methodology is a novel bottom-up approach relying mostly on anthropometric constraints and is facilitated by our research in the fields of face, skin and hands detection. Experimental results and comparison with state-of-the-art methodologies demonstrate the success of our approach

    Texture and Colour in Image Analysis

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    Research in colour and texture has experienced major changes in the last few years. This book presents some recent advances in the field, specifically in the theory and applications of colour texture analysis. This volume also features benchmarks, comparative evaluations and reviews

    A theory of information processing for machine visual perception: inspiration from psychology, formal analysis and applications

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    Tesis doctoral inédita leída en la Universidad Autónoma de Madrid, Escuela Politécnica Superior, Departamento de Ingeniería Informática. Fecha de lectura : 20-09-201

    Pattern Recognition

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    A wealth of advanced pattern recognition algorithms are emerging from the interdiscipline between technologies of effective visual features and the human-brain cognition process. Effective visual features are made possible through the rapid developments in appropriate sensor equipments, novel filter designs, and viable information processing architectures. While the understanding of human-brain cognition process broadens the way in which the computer can perform pattern recognition tasks. The present book is intended to collect representative researches around the globe focusing on low-level vision, filter design, features and image descriptors, data mining and analysis, and biologically inspired algorithms. The 27 chapters coved in this book disclose recent advances and new ideas in promoting the techniques, technology and applications of pattern recognition

    True single-cell proteomics using advanced ion mobility mass spectrometry

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    In this thesis, I present the development of a novel mass spectrometry (MS) platform and scan modes in conjunction with a versatile and robust liquid chromatography (LC) platform, which addresses current sensitivity and robustness limitations in MS-based proteomics. I demonstrate how this technology benefits the high-speed and ultra-high sensitivity proteomics studies on a large scale. This culminated in the first of its kind label-free MS-based single-cell proteomics platform and its application to spatial tissue proteomics. I also investigate the vastly underexplored ‘dark matter’ of the proteome, validating novel microproteins that contribute to human cellular function. First, we developed a novel trapped ion mobility spectrometry (TIMS) platform for proteomics applications, which multiplies sequencing speed and sensitivity by ‘parallel accumulation – serial fragmentation’ (PASEF) and applied it to first high-sensitivity and large-scale projects in the biomedical arena. Next, to explore the collisional cross section (CCS) dimension in TIMS, we measured over 1 million peptide CCS values, which enabled us to train a deep learning model for CCS prediction solely based on the linear amino acid sequence. We also translated the principles of TIMS and PASEF to the field of lipidomics, highlighting parallel benefits in terms of throughput and sensitivity. The core of my PhD is the development of a robust ultra-high sensitivity LC-MS platform for the high-throughput analysis of single-cell proteomes. Improvements in ion transfer efficiency, robust, very low flow LC and a PASEF data independent acquisition scan mode together increased measurement sensitivity by up to 100-fold. We quantified single-cell proteomes to a depth of up to 1,400 proteins per cell. A fundamental result from the comparisons to single-cell RNA sequencing data revealed that single cells have a stable core proteome, whereas the transcriptome is dominated by Poisson noise, emphasizing the need for both complementary technologies. Building on our achievements with the single-cell proteomics technology, we elucidated the image-guided spatial and cell-type resolved proteome in whole organs and tissues from minute sample amounts. We combined clearing of rodent and human organs, unbiased 3D-imaging, target tissue identification, isolation and MS-based unbiased proteomics to describe early-stage β-amyloid plaque proteome profiles in a disease model of familial Alzheimer’s. Automated artificial intelligence driven isolation and pooling of single cells of the same phenotype allowed us to analyze the cell-type resolved proteome of cancer tissues, revealing a remarkable spatial difference in the proteome. Last, we systematically elucidated pervasive translation of noncanonical human open reading frames combining state-of-the art ribosome profiling, CRISPR screens, imaging and MS-based proteomics. We performed unbiased analysis of small novel proteins and prove their physical existence by LC-MS as HLA peptides, essential interaction partners of protein complexes and cellular function

    Perceção e arquitectura de software para robótica móvel

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    Doutoramento em Ciências da ComputaçãoWhen developing software for autonomous mobile robots, one has to inevitably tackle some kind of perception. Moreover, when dealing with agents that possess some level of reasoning for executing their actions, there is the need to model the environment and the robot internal state in a way that it represents the scenario in which the robot operates. Inserted in the ATRI group, part of the IEETA research unit at Aveiro University, this work uses two of the projects of the group as test bed, particularly in the scenario of robotic soccer with real robots. With the main objective of developing algorithms for sensor and information fusion that could be used e ectively on these teams, several state of the art approaches were studied, implemented and adapted to each of the robot types. Within the MSL RoboCup team CAMBADA, the main focus was the perception of ball and obstacles, with the creation of models capable of providing extended information so that the reasoning of the robot can be ever more e ective. To achieve it, several methodologies were analyzed, implemented, compared and improved. Concerning the ball, an analysis of ltering methodologies for stabilization of its position and estimation of its velocity was performed. Also, with the goal keeper in mind, work has been done to provide it with information of aerial balls. As for obstacles, a new de nition of the way they are perceived by the vision and the type of information provided was created, as well as a methodology for identifying which of the obstacles are team mates. Also, a tracking algorithm was developed, which ultimately assigned each of the obstacles a unique identi er. Associated with the improvement of the obstacles perception, a new algorithm of estimating reactive obstacle avoidance was created. In the context of the SPL RoboCup team Portuguese Team, besides the inevitable adaptation of many of the algorithms already developed for sensor and information fusion and considering that it was recently created, the objective was to create a sustainable software architecture that could be the base for future modular development. The software architecture created is based on a series of di erent processes and the means of communication among them. All processes were created or adapted for the new architecture and a base set of roles and behaviors was de ned during this work to achieve a base functional framework. In terms of perception, the main focus was to de ne a projection model and camera pose extraction that could provide information in metric coordinates. The second main objective was to adapt the CAMBADA localization algorithm to work on the NAO robots, considering all the limitations it presents when comparing to the MSL team, especially in terms of computational resources. A set of support tools were developed or improved in order to support the test and development in both teams. In general, the work developed during this thesis improved the performance of the teams during play and also the e ectiveness of the developers team when in development and test phases.Durante o desenvolvimento de software para robôs autónomos móveis, e inevitavelmente necessário lidar com algum tipo de perceção. Al em disso, ao lidar com agentes que possuem algum tipo de raciocínio para executar as suas ações, há a necessidade de modelar o ambiente e o estado interno do robô de forma a representar o cenário onde o robô opera. Inserido no grupo ATRI, integrado na unidade de investigação IEETA da Universidade de Aveiro, este trabalho usa dois dos projetos do grupo como plataformas de teste, particularmente no cenário de futebol robótico com robôs reais. Com o principal objetivo de desenvolver algoritmos para fusão sensorial e de informação que possam ser usados eficazmente nestas equipas, v arias abordagens de estado da arte foram estudadas, implementadas e adaptadas para cada tipo de robôs. No âmbito da equipa de RoboCup MSL, CAMBADA, o principal foco foi a perceção da bola e obstáculos, com a criação de modelos capazes de providenciar informação estendida para que o raciocino do robô possa ser cada vez mais eficaz. Para o alcançar, v arias metodologias foram analisadas, implementadas, comparadas e melhoradas. Em relação a bola, foi efetuada uma análise de metodologias de filtragem para estabilização da sua posição e estimação da sua velocidade. Tendo o guarda-redes em mente, foi também realizado trabalho para providenciar informação de bolas no ar. Quanto aos obstáculos, foi criada uma nova definição para a forma como são detetados pela visão e para o tipo de informação fornecida, bem como uma metodologia para identificar quais dos obstáculos são colegas de equipa. Além disso foi desenvolvido um algoritmo de rastreamento que, no final, atribui um identicador único a cada obstáculo. Associado a melhoria na perceção dos obstáculos foi criado um novo algoritmo para realizar desvio reativo de obstáculos. No contexto da equipa de RoboCup SPL, Portuguese Team, al em da inevitável adaptação de vários dos algoritmos j a desenvolvidos para fusão sensorial e de informação, tendo em conta que foi recentemente criada, o objetivo foi criar uma arquitetura sustentável de software que possa ser a base para futuro desenvolvimento modular. A arquitetura de software criada e baseada numa série de processos diferentes e métodos de comunicação entre eles. Todos os processos foram criados ou adaptados para a nova arquitetura e um conjunto base de papeis e comportamentos foi definido para obter uma framework funcional base. Em termos de perceção, o principal foco foi a definição de um modelo de projeção e extração de pose da câmara que consiga providenciar informação em coordenadas métricas. O segundo objetivo principal era adaptar o algoritmo de localização da CAMBADA para funcionar nos robôs NAO, considerando todas as limitações apresentadas quando comparando com a equipa MSL, principalmente em termos de recursos computacionais. Um conjunto de ferramentas de suporte foram desenvolvidas ou melhoradas para auxiliar o teste e desenvolvimento em ambas as equipas. Em geral, o trabalho desenvolvido durante esta tese melhorou o desempenho da equipas durante os jogos e também a eficácia da equipa de programação durante as fases de desenvolvimento e teste

    Irish Machine Vision and Image Processing Conference Proceedings 2017

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