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Obolensky, Nicolas. "Kalman filtering methods for moving vehicle tracking." [Gainesville, Fla.] : University of Florida, 2002. http://purl.fcla.edu/fcla/etd/UFE1001174.
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Shaikh, Meher Talat. "Automatic Identification and Tracking of Retraction Fibers in Time-Lapse Microscopy." Diss., CLICK HERE for online access, 2010. http://contentdm.lib.byu.edu/ETD/image/etd3454.pdf.
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Doyle, Jason Emory. "Automatic Dynamic Tracking of Horse Head Facial Features in Video Using Image Processing Techniques." Thesis, Virginia Tech, 2019. http://hdl.handle.net/10919/87582.
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The wellbeing of horses is very important to their care takers, trainers, veterinarians, and owners. This thesis describes the development of a non-invasive image processing technique that allows for automatic detection and tracking of horse head and ear motion, respectively, in videos or camera feed, both of which may provide indications of horse pain, stress, or well-being. The algorithm developed here can automatically detect and track head motion and ear motion, respectively, in videos of a standing horse. Results demonstrating the technique for nine different horses are presented, where the data from the algorithm is utilized to plot absolute motion vs. time, velocity vs. time, and acceleration vs. time for the head and ear motion, respectively, of a variety of horses and ponies. Two-dimensional plotting of x and y motion over time is also presented. Additionally, results of pilot work in eye detection in light colored horses is also presented. Detection of pain in horses is particularly difficult because they are prey animals and have mechanisms to disguise their pain, and these instincts may be particularly strong in the presence of an unknown human, such as a veterinarian. Current state-of-the art for detecting pain in horses primarily involves invasive methods, such as heart rate monitors around the body, drawing blood for cortisol levels, and pressing on painful areas to elicit a response, although some work has been done for humans to sort and score photographs subjectively in terms of a "horse grimace scale." The algorithms developed in this thesis are the first that the author is aware for exploiting proven image processing approaches from other applications for development of an automatic tool for detection and tracking of horse facial indicators. The algorithms were done in common open source programs Python and OpenCV, and standard image processing approaches including Canny Edge detection Hue, Saturation, Value color filtering, and contour tracking were utilized in algorithm development. The work in this thesis provides the foundational development of a non -invasive and automatic detection and tracking program for horse head and ear motion, including demonstration of the viability of this approach using videos of standing horses. This approach lays the groundwork for robust tool development for monitoring horses non-invasively and without the required presence of humans in such applications as post-operative monitoring, foaling, evaluation of performance horses in competition and/or training, as well as for providing data for research on animal welfare, among other scenarios.MS
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Park, Man-Woo. "Automated 3D vision-based tracking of construction entities." Diss., Georgia Institute of Technology, 2012. http://hdl.handle.net/1853/45782.
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In construction sites, tracking project-related entities such as construction equipment, materials, and personnel provides useful information for productivity measurement, progress monitoring, on-site safety enhancement, and activity sequence analysis. Radio frequency technologies such as Global Positioning Systems (GPS), Radio Frequency Identification (RFID) and Ultra Wide Band (UWB) are commonly used for this purpose. However, on large-scale congested sites, deploying, maintaining and removing such systems can be costly and time-consuming because radio frequency technologies require tagging each entity to track. In addition, privacy issues can arise from tagging construction workers, which often limits the usability of these technologies on construction sites. A vision-based approach that can track moving objects in camera views can resolve these problems.
The purpose of this research is to investigate the vision-based tracking system that holds promise to overcome the limitations of existing radio frequency technologies for large-scale, congested sites. The proposed method use videos from static cameras. Stereo camera system is employed for tracking of construction entities in 3D. Once the cameras are fixed on the site, intrinsic and extrinsic camera parameters are discovered through camera calibration. The method automatically detects and tracks interested objects such as workers and equipment in each camera view, which generates 2D pixel coordinates of tracked objects. The 2D pixel coordinates are converted to 3D real-world coordinates based on calibration. The method proposed in this research was implemented in .NET Framework 4.0 environment, and tested on the real videos of construction sites. The test results indicated that the methods could locate construction entities with accuracy comparable to GPS.
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Katta, Pradeep. "Integrating depth and intensity information for vision-based head tracking." abstract and full text PDF (UNR users only), 2008. http://0-gateway.proquest.com.innopac.library.unr.edu/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:1456416.
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Preussner, Jonathan J. "Multiple target tracker and human classifier for radar application." [Gainesville, Fla.] : University of Florida, 2005. http://purl.fcla.edu/fcla/etd/UFE0009821.
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Clark, Daniel S. "Object detection and tracking using a parts-based approach /." Link to online version, 2005. https://ritdml.rit.edu/dspace/handle/1850/1167.
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Tissainayagam, Prithiviraj 1967. "Visual tracking : development, performance evaluation, and motion model switching." Monash University, Dept. of Electrical and Computer Systems Engineering, 2001. http://arrow.monash.edu.au/hdl/1959.1/8944.
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Tanase, Cristina-Madalina. "Multi-person tracking system for complex outdoor environments." Thesis, Uppsala universitet, Institutionen för informationsteknologi, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-245082.
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The thesis represents the research in the domain of modern video tracking systems and presents the details of the implementation of such a system. Video surveillance is a high point of interest and it relies on robust systems that interconnect several critical modules: data acquisition, data processing, background modeling, foreground detection and multiple object tracking. The present work analyzes different state of the art methods that are suitable for each module. The emphasis of the thesis is on the background subtraction stage, as the final accuracy and performance of the person tracking dramatically dependent on it. The experimental results show the performance of four different foreground detection algorithms, including two variations of self-organizing feature maps for background modeling, a machine learning technique. The undertaken work provides a comprehensive view of the actual state of the research in the foreground detection field and multiple object tracking and offers solution for common problems that occur when tracking in complex scenes. The chosen data set for experiments covers extremely different and complex scenes (outdoor environments) that allow a detailed study of the appropriate approaches and emphasize the weaknesses and strengths of each algorithm. The proposed system handles problems like: dynamic backgrounds, illumination changes, camouflage, cast shadows, frequent occlusions and crowded scenes. The tracking obtains a maximum Multiple Object Tracking Accuracy of 92,5% for the standard video sequence MWT and a minimum of 32,3% for an extremely difficult sequence that challenges every method.
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Neumann, Markus. "Automatic multimodal real-time tracking for image plane alignment in interventional Magnetic Resonance Imaging." Phd thesis, Université de Strasbourg, 2014. http://tel.archives-ouvertes.fr/tel-01038023.
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Interventional magnetic resonance imaging (MRI) aims at performing minimally invasive percutaneous interventions, such as tumor ablations and biopsies, under MRI guidance. During such interventions, the acquired MR image planes are typically aligned to the surgical instrument (needle) axis and to surrounding anatomical structures of interest in order to efficiently monitor the advancement in real-time of the instrument inside the patient's body. Object tracking inside the MRI is expected to facilitate and accelerate MR-guided interventions by allowing to automatically align the image planes to the surgical instrument. In this PhD thesis, an image-based workflow is proposed and refined for automatic image plane alignment. An automatic tracking workflow was developed, performing detection and tracking of a passive marker directly in clinical real-time images. This tracking workflow is designed for fully automated image plane alignment, with minimization of tracking-dedicated time. Its main drawback is its inherent dependence on the slow clinical MRI update rate. First, the addition of motion estimation and prediction with a Kalman filter was investigated and improved the workflow tracking performance. Second, a complementary optical sensor was used for multi-sensor tracking in order to decouple the tracking update rate from the MR image acquisition rate. Performance of the workflow was evaluated with both computer simulations and experiments using an MR compatible testbed. Results show a high robustness of the multi-sensor tracking approach for dynamic image plane alignment, due to the combination of the individual strengths of each sensor.
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Mozaffari, Maaref Mohammad Hamed. "A Real-Time and Automatic Ultrasound-Enhanced Multimodal Second Language Training System: A Deep Learning Approach." Thesis, Université d'Ottawa / University of Ottawa, 2020. http://hdl.handle.net/10393/40477.
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The critical role of language pronunciation in communicative competence is significant, especially for second language learners. Despite renewed awareness of the importance of articulation, it remains a challenge for instructors to handle the pronunciation needs of language learners. There are relatively scarce pedagogical tools for pronunciation teaching and learning, such as inefficient, traditional pronunciation instructions like listening and repeating. Recently, electronic visual feedback (EVF) systems (e.g., medical ultrasound imaging) have been exploited in new approaches in such a way that they could be effectively incorporated in a range of teaching and learning contexts. Evaluation of ultrasound-enhanced methods for pronunciation training, such as multimodal methods, has asserted that visualizing articulator’s system as biofeedback to language learners might improve the efficiency of articulation learning. Despite the recent successful usage of multimodal techniques for pronunciation training, manual works and human manipulation are inevitable in many stages of those systems. Furthermore, recognizing tongue shape in noisy and low-contrast ultrasound images is a challenging job, especially for non-expert users in real-time applications. On the other hand, our user study revealed that users could not perceive the placement of their tongue inside the mouth comfortably just by watching pre-recorded videos.
Machine learning is a subset of Artificial Intelligence (AI), where machines can learn by experiencing and acquiring skills without human involvement. Inspired by the functionality of the human brain, deep artificial neural networks learn from large amounts of data to perform a task repeatedly. Deep learning-based methods in many computer vision tasks have emerged as the dominant paradigm in recent years. Deep learning methods are powerful in automatic learning of a new job, while unlike traditional image processing methods, they are capable of dealing with many challenges such as object occlusion, transformation variant, and background artifacts. In this dissertation, we implemented a guided language pronunciation training system, benefits from the strengths of deep learning techniques. Our modular system attempts to provide a fully automatic and real-time language pronunciation training tool using ultrasound-enhanced augmented reality. Qualitatively and quantitatively assessments indicate an exceptional performance for our system in terms of flexibility, generalization, robustness, and autonomy outperformed previous techniques. Using our ultrasound-enhanced system, a language learner can observe her/his tongue movements during real-time speech, superimposed on her/his face automatically.
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Arif, Omar. "Robust target localization and segmentation using statistical methods." Diss., Georgia Institute of Technology, 2010. http://hdl.handle.net/1853/33882.
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This thesis aims to contribute to the area of visual tracking, which is the process of identifying an object of interest through a sequence of successive images. The thesis explores kernel-based statistical methods, which map the data to a higher dimensional space. A pre-image framework is provided to find the mapping from the embedding space to the input space for several manifold learning and dimensional learning algorithms. Two algorithms are developed for visual tracking that are robust to noise and occlusions. In the first algorithm, a kernel PCA-based eigenspace representation is used. The de-noising and clustering capabilities of the kernel PCA procedure lead to a robust algorithm. This framework is extended to incorporate the background information in an energy based formulation, which is minimized using graph cut and to track multiple objects using a single learned model. In the second method, a robust density comparison framework is developed that is applied to visual tracking, where an object is tracked by minimizing the distance between a model distribution and given candidate distributions. The superior performance of kernel-based algorithms comes at a price of increased storage and computational requirements. A novel method is developed that takes advantage of the universal approximation capabilities of generalized radial basis function neural networks to reduce the computational and storage requirements for kernel-based methods.
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Dias, Fábio Augusto Salve. "Generalização do ritmo visual e problemas de rastreamento de imagens desportivas." [s.n.], 2009. http://repositorio.unicamp.br/jspui/handle/REPOSIP/275918.
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Orientador: Neucimar Jeronimo LeiteDissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Computação
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Resumo: O rastreamento de objetos em imagens de vídeo está se tornando cada vez mais popular, nos mais diversos contextos, possibilitando a obtenção de informações que, de outra maneira, seriam muito trabalhosas ou mesmo impossíveis de serem obtidas. Entretanto, a grande maioria dos métodos presentes na literatura realiza o rastreamento no domínio da imagem, não no domínio tridimensional natural do problema. No contexto de imagens desportivas, onde movimentos rápidos, similaridades cromáticas entre jogadores do mesmo time e oclusões são significativas, a utilização do domínio tridimensional é particularmente interessante. Este trabalho tem como premissa básica a realização do rastreamento em um domínio tridimensional, partindo de determinadas hipóteses, plausíveis em um contexto desportivo, visando ao rastreamento automático dos jogadores em atividades desportivas. Generalizamos o conceito de ritmo visual, um método de amostragem vastamente utilizado para detecção de cortes em imagens de vídeos, e o utilizamos para efetuar o rastreamento, resultando em um método simples, intuitivo e automático quando seus pré-requisitos são atendidos. Para possibilitar a utilização da generalização do ritmo visual, desenvolvemos ainda algoritmos para identificação de objetos em movimento, calibração de câmeras e reconstrução tridimensional, além de um algoritmo baseado em grafos para a segmentação da trajetória de cada objeto em movimento, utilizando a informação obtida através do ritmo visual. Apresentamos resultados experimentais da utilização do método proposto em vídeos de eventos desportivos e coletados em laboratório, incluindo casos nos quais as condições ideais de utilização não são atendidas, causando falhas no método
Abstract: The automatic tracking in the video images is becoming increasingly popular, in many different contexts, making available information that, otherwise, would be very laborious or even impossible to be obtained. However, most of the methods perform the tracking in the image domain not in the natural three-dimensional domain. For sports images, with rapid motions, color similarity and occlusions, the three-dimensional approach is an interesting alternative. In this work, we introduce a tracking method in the three-dimensional domain, based on some requirements, feasible in the sports context, aiming fully automatic tracking of the players. We also introduce the generalization of the visual rhythm concept and its use to the tracking problem, leading to a simple, intuitive, and automatic method. To use the generalization of the visual rhythm, we also developed algorithms to detect moving objects, camera calibration and three-dimensional reconstruction, and an algorithm based on graphs for the segmentation of the trajectory of each moving object in the scene, considering information obtained through the visual rhythm. We also show experimental results of the proposed method, in sports images and controlled environments, including cases where not all the requirements are fulfilled, yielding failures of the proposed approach
Mestrado
Ciência da Computação
Mestre em Ciência da Computação
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Fallah, Haghmohammadi Hamidreza. "Fever Detection for Dynamic Human Environment Using Sensor Fusion." Thesis, Université d'Ottawa / University of Ottawa, 2018. http://hdl.handle.net/10393/37332.
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The objective of this thesis is to present an algorithm for processing infrared images and accomplishing automatic detection and path tracking of moving subjects with fever. The detection is based on two main features: the distinction between the geometry of a human face and other objects in the field of view of the camera and the temperature of the radiating object. These features are used for tracking the identified person with fever. The position of camera with respect to direction of motion the walkers appeared to be critical in this process. Infrared thermography is a remote sensing technique used to measure temperatures based on emitted infrared radiation. This application may be used for fever screening in major public places such as airports and hospitals. For this study, we first look at human body and objects in a line of view with different temperatures that would be higher than the normal human body temperature (37.8C at morning and 38.3C at evening). As a part of the experimental study, two humans with different body temperatures walking a path were subjected to automatic fever detection applied for tracking the detected human with fever. The algorithm consists of image processing to threshold objects based on the temperature and template matching used for fever detection in a dynamic human environment.
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Higashino, Wilson Akio 1981. "Estudo comparativo de algoritmos de subtração de fundo em sequencias de imagens." [s.n.], 2006. http://repositorio.unicamp.br/jspui/handle/REPOSIP/276479.
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Orientador: Ricardo de Oliveira AnidoDissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Computação
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Resumo: Existe uma grande demanda de sistemas de captura de movimentos robustos e confiáveis, sejam eles para aplicações comerciais, para o cumprimento da lei ou monitoramento de territórios. A obtenção e instalação de câmaras de vídeo são hoje muito baratas; os maiores custos estão relacionados às pessoas que vêem as imagens, as interpretam e tiram conclusões. Pessoas são também inerentemente passíveis a falhas: não conseguem manter a atenção por longos períodos de tempo, e muitos menos lidar com grandes quantidades de informações. A detecção de objetos em uma seqüência de vídeo é etapa primordial em grande parte destes sistemas. Exercendo um papel fundamental, os algoritmos de subtração de fundo já demonstraram um enorme potencial para essa tarefa. No entanto, muitos problemas ainda estão em aberto e são alvos de discussões e pesquisa. A compreensão do alcance e limitações destes algoritmos é muito importante para que, na construção de um sistema de visão computacional, possamos selecionar aquele que melhor atenda os requisitos. O objetivo deste trabalho é demonstrar qual é o estado da arte destes algoritmos e selecionar os mais relevantes para uma comparação sob diferentes situações reais, fornecendo subsídios para o seu correto entendimento
Abstract: There is a great demand for robust and trustful movement capture systems, like commercial, law enforcement or territory monitoring applications. Acquisition and installation of video cameras is very cheap nowadays; expensive are the people that watch, interpret and draw conclusions from images. People are also prone to failure: they are unable to pay attention for long periods of time and cannot handle large amounts of information. Object detection in a video sequence is an important step in those systems. Playing a main role, the background subtraction algorithms have already shown a great potential for this task. However, there are a lot of problems that are still unresolved and are subject of discussions and research. The understanding of the algorithms' range and limitations is very important to allow the right selection of one of them, given a situation. The purpose of this work is to demonstrate the state-of-the-art of this algorithms and to select the most relevant ones to compare them in different real life situations, supplying informations for their correct understanding
Mestrado
Visão Computacional
Mestre em Ciência da Computação
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Souza, Rafael Henrique Castanheira de. "Rastreamento de animais por imagens de video em experimentos de laboratorio." [s.n.], 2008. http://repositorio.unicamp.br/jspui/handle/REPOSIP/276085.
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Orientador: Neucimar Jeronimo LeiteDissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Computação
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Resumo: O rastreamento automático de animais permite um estudo comportamental mais consistente e rápido do que o feito normalmente utilizando-se registro manual dos parâmetros de experimentos em biologia. O registro automático é realizado por um sistema analisador de imagens que, a partir de uma sequência contínua de quadros de um vídeo, calcula uma série de descritores associados ao movimento das cobaias. O objetivo deste trabalho é criar um sistema de rastreamento para experimentos de laboratório, levando em conta múltiplas cobaias que podem vir a sofrer oclusão. Além disso, pretende-se que o modelo de rastreamento proposto seja robusto a baixa qualidade do vídeo, além de ser geral o suficiente para ser adaptado a outros experimentos com poucas modificações
Abstract: The automatic tracking of animals allows a quicker and more consistent analysis of behaviour than the usual manual method for registering experimental parameters in biology. The automatic register of parameters is performed by a system that analyses a sequence of images and computes a number of descriptors that characterizes the behaviour of each target. Our objective is to create a framework for tracking in biology experiments, with multiple targets that may suffer occlusion. Besides, we intend to create a framework that can deal with low-quality videos and capable of being adapted to other classes of tracking
Mestrado
Processamento de Imagens
Mestre em Ciência da Computação
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Freitas, Greice Martins de. "Rastreamento de objetos em vídeos e separação em classes." [s.n.], 2010. http://repositorio.unicamp.br/jspui/handle/REPOSIP/258882.
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Orientador: Clésio Luis TozziDissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Elétrica e de Computação
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Resumo: A crescente utilização de câmeras de vídeo para o monitoramento de ambientes, auxiliando no controle de entrada, saída e trânsito de indivíduos ou veículos tem aumentado a busca por sistemas visando a automatização do processo de monitoramento por vídeos. Como requisitos para estes sistemas identificam-se o tratamento da entrada e saída de objetos na cena, variações na forma e movimentação dos alvos seguidos, interações entre os alvos como encontros e separações, variações na iluminação da cena e o tratamento de ruídos presentes no vídeo. O presente trabalho analisa e avalia as principais etapas de um sistema de rastreamento de múltiplos objetos através de uma câmera de vídeo fixa e propõe um sistema de rastreamento baseado em sistemas encontrados na literatura. O sistema proposto é composto de três fases: identificação do foreground através de técnicas de subtração de fundo; associação de objetos quadro a quadro através de métricas de cor, área e posição do centróide - com o auxílio da aplicação do filtro de Kalman - e, finalmente, classificação dos objetos a cada quadro segundo um sistema de gerenciamento de objetos. Com o objetivo de verificar a eficiência do sistema de rastreamento proposto, testes foram realizados utilizando vídeos das bases de dados PETS e CAVIAR. A etapa de subtração de fundo foi avaliada através da comparação do modelo Eigenbackground, utilizado no presente sistema, com o modelo Mistura de Gaussianas, modelo de subtração de fundo mais utilizado em sistemas de rastreamento. O sistema de gerenciamento de objeto foi avaliado por meio da classificação e contagem manual dos objetos a cada quadro do vídeo. Estes resultados foram comparados à saída do sistema de gerenciamento de objetos. Os resultados obtidos mostraram que o sistema de rastreamento proposto foi capaz de reconhecer e rastrear objetos em movimento em sequências de vídeos, lidando com oclusões e separações, mostrando adequabilidade para aplicação em sistemas de segurança em tempo real
Abstract: There are immediate needs for the use of video cameras in environment monitoring, which can be verified by the task of assisting the entrance, exit and transit registering of people or vehicles in a area. In this context, automated surveillance systems based on video images are increasingly gaining interest. As requisites for these systems, it can be identified the treatment of entrances and exits of objects on a scene, shape variation and movement of followed targets, interactions between targets (such as meetings and splits), lighting variations and video noises. This work analyses and evaluates the main steps of a multiple target tracking system through a fixed video camera and proposes a tracking system based on approaches found in the literature. The proposed system is composed of three steps: foreground identification through background subtraction techniques; object association through color, area and centroid position matching, by using the Kalman filter to estimate the object's position in the next frame, and, lastly, object classification according an object management system. In order to assess the efficiency of the proposed tracking system, tests were performed by using videos from PETS and CAVIAR datasets. The background subtraction step was evaluated by means of a comparison between the Eigenbackground model, used in the proposed tracking system, and the Mixture of Gaussians model, one of the most used background subtraction models. The object management system was evaluated through manual classification and counting of objects on each video frame. These results were compared with the output of the object management system. The obtained results showed that the proposed tracking system was able to recognize and track objects in movement on videos, as well as dealing with occlusions and separations, and, at the same time, encouraging future studies in order for its application on real time security systems
Mestrado
Engenharia de Computação
Mestre em Engenharia Elétrica
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Khorshidi, Mohammad Ali. "Live Single Cell Imaging and Analysis Using Microfluidic Devices." Doctoral thesis, KTH, Proteomik och nanobioteknologi, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-129278.
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Today many cell biological techniques study large cell populations where an average estimate of individual cells’ behavior is observed. On the other hand, single cell analysis is required for studying functional heterogeneities between cells within populations. This thesis presents work that combines the use of microfluidic devices, optical microscopy and automated image analysis to design various cell biological assays with single cell resolution including cell proliferation, clonal expansion, cell migration, cell-cell interaction and cell viability tracking. In fact, automated high throughput single cell techniques enable new studies in cell biology which are not possible with conventional techniques. In order to automatically track dynamic behavior of single cells, we developed a microwell based device as well as a droplet microfluidic platform. These high throughput microfluidic assays allow automated time-lapse imaging of encapsulated single cells in micro droplets or confined cells inside microwells. Algorithms for automatic quantification of cells in individual microwells and micro droplets are developed and used for the analysis of cell viability and clonal expansion. The automatic counting protocols include several image analysis steps, e.g. segmentation, feature extraction and classification. The automatic quantification results were evaluated by comparing with manual counting and revealed a high success rate. In combination these automatic cell counting protocols and our microfluidic platforms can provide statistical information to better understand behavior of cells at the individual level under various conditions or treatments in vitro exemplified by the analysis of function and regulation of immune cells. Thus, together these tools can be used for developing new cellular imaging assays with resolution at the single cell level. To automatically characterize transient migration behavior of natural killer (NK) cells compartmentalized in microwells, we developed a method for single cell tracking. Time-lapse imaging showed that the NK cells often exhibited periods of high motility, interrupted with periods of slow migration or complete arrest. These transient migration arrest periods (TMAPs) often overlapped with periods of conjugations between NK cells and target cells. Such conjugation periods sometimes led to cell-mediated killing of target cells. Analysis of cytotoxic response of NK cells revealed that a small sub-class of NK cells called serial killers was able to kill several target cells. In order to determine a starting time point for cell-cell interaction, a novel technique based on ultrasound was developed to aggregate NK and target cells into the center of the microwells. Therefore, these assays can be used to automatically and rapidly assess functional and migration behavior of cells to detect differences between health and disease or the influence of drugs. The work presented in this thesis gives good examples of how microfluidic devices combined with automated imaging and image analysis can be helpful to address cell biological questions where single cell resolution is necessary.QC 20130927
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Vitor, Giovani Bernardes 1985. "Rastreamento de alvo móvel em mono-visão aplicado no sistema de navegação autônoma utilizando GPU." [s.n.], 2010. http://repositorio.unicamp.br/jspui/handle/REPOSIP/264975.
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Orientador: Janito Vaqueiro FerreiraDissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Mecânica
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Resumo: O sistema de visão computacional é bastante útil em diversas aplicações de veículos autônomos, como em geração de mapas, desvio de obstáculos, tarefas de posicionamento e rastreamento de alvos. Além disso, a visão computacional pode proporcionar um ganho significativo na confiabilidade, versatilidade e precisão das tarefas robóticas, questões cruciais na maioria das aplicações reais. O presente trabalho tem como objetivo principal o desenvolvimento de uma metodologia de controle servo visual em veículos robóticos terrestres para a realização de rastreamento e perseguição de um alvo. O procedimento de rastreamento é baseado na correspondência da região alvo entre a seqüência de imagens, e a perseguição pela geração do movimento de navegação baseado nas informações da região alvo. Dentre os aspectos que contribuem para a solução do procedimento de rastreamento proposto, considera-se o uso das técnicas de processamento de imagens como filtro KNN, filtro Sobel, filtro HMIN e transformada Watershed que unidas proporcionam a robustez desejada para a solução. No entanto, esta não é uma técnica compatível com sistema de tempo real. Deste modo, tais algoritmos foram modelados para processamento paralelo em placas gráficas utilizando CUDA. Experimentos em ambientes reais foram analisados, apresentando diversos resultados para o procedimento de rastreamento, bem como validando a utilização das GPU's para acelerar o processamento do sistema de visão computacional
Abstract: The computer vision system is useful in several applications of autonomous vehicles, such as map generation, obstacle avoidance tasks, positioning tasks and target tracking. Furthermore, computer vision can provide a significant gain in reliability, versatility and accuracy of robotic tasks, which are important concerns in most applications. The present work aims at the development of a visual servo control method in ground robotic vehicles to perform tracking and follow of a target. The procedure for tracking is based on the correspondence between the target region sequence of images, and persecution by the generation of motion based navigation of information from target region. Among the aspects that contribute to the solution of the proposed tracking procedure, we consider the use of imaging techniques such as KNN filter, Sobel filter, HMIN filter and Watershed transform that together provide the desired robustness for the solution. However, this is not a technique compatible with real-time system. Thus, these algorithms were modeled for parallel processing on graphics cards using CUDA. Experiments in real environments were analyzed showed different results for the procedure for tracking and validating the use of GPU's to accelerate the processing of computer vision system
Mestrado
Mecanica dos Sólidos e Projeto Mecanico
Mestre em Engenharia Mecânica
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Elmowafy, Osama Mohammed Elsayed. "Image processing systems for TV image tracking." Thesis, University of Kent, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.310164.
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Parr, T. C. "Automatic vehicle guidance via image processing." Thesis, University of Manchester, 1993. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.488385.
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CUNHA, CLAUDIO MARCIO PEREIRA DA. "PARTICLE TRACKING VELOCIMETRY USING DIGITAL IMAGE PROCESSING." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 1993. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=24882@1.
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Foi desenvolvido um sistema de mediação de campo completo de velocidade de escoamento de fluidos. A técnica empregada é conhecida como Particle Tracking Velocimetry (PTV). As medidas foram determinadas a partir de imagens de trajetórias de partículas em suspensão no fluido. As imagens foram digitalizadas e processadas automaticamente em um microcomputador. O processamento foi feito por um software dedicado que identifica as trajetórias e calcula as velocidades associadas. Para comparação dos resultados obtidos o sistema desenvolvido foi aplicado a um escoamento cujo perfil de velocidade é conhecido. Foram analisadas as influências nos resultados de características das imagens e de seu processamento.A system for full field velocity measurement in fluid flows has been developed. The technique employed is known as Particle Tracking Velocimetry (PTV). Velocity measurements have been performed based on images of particles seeded in the fluid. The images have been digitized and automatically processed in a micro-computer. Image processing tecniques have been employed using a dedicated software that identifies particles trajectories and calculates associated velocities. To compare the results obtained, the system developed was applied to test flows with known velocity profiles. A detailed uncertainty analisys developed revealed the influence. On the results. of the image characteristics and processing procedures.
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Chen, Jialing. "Automatic computational techniques for image processing problems." Thesis, University of Dundee, 2018. https://discovery.dundee.ac.uk/en/studentTheses/ec173c99-bb52-4c2a-878a-06c04feabd04.
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This thesis presents the research of my PhD, which is the study of the mathematical image processing techniques and their application. The key point for this work is the automation of these techniques. We begin by introducing a traditional segmentation algorithm, the Otsu’s method, to study the automatic image thresholding technique, where we develop a new automatic global thresholding method for distinguishing different types of cell, and apply the method in drug development industry for high content screening. Starting from the traditional statistics-based method, we then investigate a more mathematical model, the total-variation (TV) method for image denoising and deblurring problems. In traditional TV-based models, it is not easy to systemically provide a choice of parameters for the system. Inspired by the ideas from machine learning, we design a new learning-based TV model where the parameters can be derived automatically via optimal control. However, only one optimal solution is given by this model. Finally we combine our model with a newly-invented evolutionary algorithm where allows us to study all the possible optimal solutions and compare the differences they bring to the output images of our model. The experimental results have shown effectiveness on image denosing and deblurring problems comparing with both traditional and existing learning-based TV methods.
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Lacey, Anthony John. "The automatic extraction and tracking of moving image features." Thesis, University of Sheffield, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.286907.
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Ferro, Tyler. "Automatic Image Processing and Conversion to Tactile Graphics." VCU Scholars Compass, 2018. https://scholarscompass.vcu.edu/etd/5469.
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Graphical information has become a critical method for portraying information for education, work and personal tasks and decisions. Unfortunately there are currently limited means of providing this information to individuals who are blind or visually impaired: alternate text is frequently missing, and accessible tactile diagrams tend to be time consuming to make and require expertise in order for them to be interpretable (which may be costly to the user and/or impossible to get). The aim of this project is to provide an accessible system to automatically generate tactile graphics for those who need to interpret information contained in visual images. Previous automatic conversion methods have not been especially successful and are not used in normal practice, possibly because they have not taken advantage of current advances in the field of image processing. In the preliminary work, we systematically look at the myriad of image segmentation methods that exist as part of the conversion process. For those techniques, previous researchers have often compared the results to the “gold standard” of human segmentation to evaluate their success. However, there are important difference between this “gold standard” and what is needed for tactile graphics. Key steps by professionals who create tactile diagrams are simplification so that the information is manageable to extract through the tactile sense, elimination of perspective as it is difficult to interpret tactually, and possible spreading of information across multiple diagrams. Planned work is to examine more closely the underlying themes to the myriad of algorithm are relevant for tactile diagrams. Future work, will also involve taking the initially segmented image, simplifying it further by removing “unimportant” detail so that it is manageable by the tactile system and removing perspective based on geometric information found in the image.
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Van, Blommestein Donald Lloyd. "Automating a labour performance measurement and risk assessment: an evaluation of methods for a computer vision based system." Thesis, Stellenbosch : Stellenbosch University, 2014. http://hdl.handle.net/10019.1/86502.
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Thesis (MScEng) Stellenbosch University, 2014ENGLISH ABSTRACT: This thesis brings together productivity and risk assessments through innovative design, development and evaluation of a unique system for retrieving and analysing data. In the past, although the link between them is well-documented, these assessments have largely been dealt with as separate antagonist entities. A broad evaluation of the existing traditional and technological support systems has been conducted to identify suitable methodologies along with a common technological platform for automation. The methodologies selected for the productivity and risk assessments were; work sampling and the revised NIOSH lifting equation respectively. The automation of these procedures is facilitated through computer vision and the use of a range imaging Kinect™ camera. The standalone C++ application integrates two tracking approaches to extract real-time positional data on the worker and the work-piece. The OpenNI and OpenCV libraries are used to perform skeletal tracking and image recognition respectively. The skeletal tracker returns positional data on specific joints of the worker, while the image recognition component, a SURF implementation, is used to identify and track a specific work-piece within the capture frame. These tracking techniques are computationally expensive. In order to enable real time execution of the program, Nvidia’s CUDA toolkit and threading building blocks have been applied to reduce the processing time. The performance measurement system is a continuous sampling derivative of work sampling. The speed of the worker’s hand movements and proximity to the work-piece are used to classify the worker in one of four possible states; busy, static, idle, or out of frame. In addition to the worker based performance measures, data relating to work-pieces are also calculated. These include the number of work-pieces processed by a specific worker, along with the average and variations in the processing times. The risk assessment is an automated approach of the revised NIOSH lifting equation. The system calculates when a worker makes and/or breaks contact with the work-piece and uses the joint locations from the skeletal tracker to calculate the variables used in the determination of the multipliers and ultimately the recommended weight limit and lifting index. The final calculation indicates whether the worker is at risk of developing a musculoskeletal disorder. Additionally the information provided on each of the multipliers highlights which elements of the lifting task contribute the most to the risk. The user-interface design ensures that the system is easy to use. The interface also displays the results of the study enabling analysts to assess worker performance at any time in real time. The automated system therefore enables analysts to respond rapidly to rectify problems. The system also reduces the complexity of performing studies and it eliminates human errors. The time and costs required to perform the studies are reduced and the system can become a permanent fixture on factory floors. The development of the automated system opens the door for further development of the system to ultimately enable more detailed assessments of productivity and risk.
AFRIKAANSE OPSOMMING: Produktiwiteit en risiko evaluerings word in hierdie tesis saam hanteer deur die innoverende ontwerp, ontwikkeling en evaluering van 'n unieke stelsel vir die meting en ontleding van data. Alhoewel die skakel tussen hulle goed gedokumenteer is, word hierdie evaluering as afsonderlike antagonistiese entiteite hanteer. 'n Breë studie van die bestaande tradisionele en tegnologiese ondersteuningstelsels is gedoen om toepaslike metodes te identifiseer, om 'n gemeenskaplike tegnologiese platform vir outomatisering daar te stel. Die metodes wat gekies is vir die produktiwiteit en risiko bepalings is onderskeidelik werk monsterneming en die hersiende NIOSH opheffing vergelyking. Die outomatisering van hierdie prosedures word gefasiliteer deur middel van rekenaar visie en die gebruik van 'n Kinect™ 3D kamera. Die selfstandige C++ program integreer ‘n dubbelvolgings benadering om in reële tyd posisionele data van die werker en die werk-stuk te kry. Die OpenNI en OpenCV biblioteke word onderskeidelik gebruik om skeletale volging en beeld erkenning uit te voer. Die skeletale volger bepaal posisionele data van spesifieke gewrigte van die werker, terwyl die beeld erkenning komponent, 'n SURF implementering gebruik om 'n spesifieke werk-stuk binne die opname raam te identifiseer en te volg. Hierdie volgings tegnieke is berekenings intensief. Om werklike tyd uitvoering van die program te verseker, is Nvidia se CUDA gereedskapstel en liggewig boublokke geimplementeer. Die produktiwiteit meting-stelsel is 'n aaneenlopende monsterneming benadering van werk monsterneming. Die spoed van die werker se handbewegings en nabyheid aan die werkstuk word gebruik om die werker te klassifiseer as in een van vier moontlike toestande; besig, staties, onaktief of buite die raam. Benewens die werker gebaseerde metings, word daar ook data oor werkstukke bereken. Dit sluit in die aantal werkstukke verwerk deur 'n spesifieke werker, sowel as die gemiddelde en variasie in verwerkings tye. Die risiko-berekening is 'n outomatiese benadering van die hersiende NIOSH opheffing vergelyking. Die stelsel bereken wanneer die werker kontak maak en/of breek met die werkstuk en maak gebruik van die gewrigsposisies wat die skeletale volger aandui om die veranderlikes wat in die vermenigvuldigers gebruik word te bepaal. Die vermenigvuldigers word gebruik om die aanbevole maksimum gewig en die opheffing indeks te bereken. Die opheffing indeks dui aan of daar ‘n risiko vir die werker is om muskuloskeletale versteuring te ontwikkel. Benewens dui die vermenigvuldigers aan watter elemente die grootste bydra tot die risiko van die opheffingstaak maak. Die gebruiker-koppelvlak-ontwerp verseker dat die stelsel maklik is om te gebruik. Die koppelvlak vertoon ook die resultate van die studie sodat ontleders op enige tyd werker prestasie kan evalueer in reële tyd. Die outomatiese stelsel stel dus ontleders in staat om vinnig te reageer sodat probleme reggestel kan word. Die stelsel verminder ook die kompleksiteit vir die uitvoering van studies en dit elimineer menslike foute. Die tyd en koste vereis om die studie te doen, word verminder en die stelsel kan ‘n permanente instelling op fabriekvloere geword. Die ontwikkeling van die outomatiese stelsel maak die deur oop vir verdere ontwikkeling van die stelsel om uiteindelik daartoe te lei dat meer gedetailleerde evaluering van produktiwiteit en risiko bepaal kan word.
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Wagner, Ross. "Image processing applied to the tracking of eye movements." Thesis, McGill University, 1989. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=55657.
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Öberg, Per. "Tracking by Image Processing in a Real Time System." Thesis, Linköping University, Department of Electrical Engineering, 2003. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-1705.
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This master's thesis develops an algorithm for tracking of cars robust enough to handle turning cars. It is implemented in the image processing environment Image Processing Application Programming Interface (IPAPI) for use with the WITAS project.
Firstly, algorithms, comparable with one currently used in the WITAS-project, are studied. The focus is on how rotation, that originates from the turning of the cars, affects tracking performance. The algorithms studied all perform an exhaustive search over a region, close to the last known position of the object being tracked, to find a match. After this, an iterative algorithm, based on the idea that a car can only rotate, translate and change scale, is introduced. The algorithm estimates the parameters describing this rotation, translation, and change of scale, iteratively. The iterative process needs a initial parameter estimate that is accurate enough for the algorithm to converge. The developed algorithm is based on an earlier publication on the subject, however the mathematical description, and deduction, of it is taken one step further than in this publication.
The iterative algorithm used performs well under the assumption that the data used fulfills some basic criteria. These demands comprises: placement of camera, template size as well as how the parameters may vary between two observations. The iterative algorithm is also potentially faster than exhaustive search methods, because few iterations are needed when the parameters change slowly. Better initial parameters should improve stability and speed of convergation. Other suggestions that could give better performance is discussed, e.g., methods to better extract the target from the surroundings.
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Jonsson, Christian. "Detection of annual rings in wood." Thesis, Linköping University, Department of Science and Technology, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-15804.
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This report describes an annual line detection algorithm for the WoodEye quality control system. The goal with the algorithm is to find the positions of annual lines on the four surfaces of a board. The purpose is to use this result to find the inner annual ring structure of the board. The work was done using image processing techniques to analyze images collected with WoodEye. The report gives the reader an insight in the requirements of quality control systems in the woodworking industry and the benefits of automated quality control versus manual inspection. The appearance and formation of annual lines are explained on a detailed level to provide insight on how the problem should be approached. A comparison between annual rings and fingerprints are made to see if ideas from this area of pattern recognition can be adapted to annual line detection. This comparison together with a study of existing methods led to the implementation of a fingerprint enhancement method. This method became a central part of the annual line detection algorithm. The annual line detection algorithm consists of two main steps; enhancing the edges of the annual rings, and tracking along the edges to form lines. Different solutions for components of the algorithm were tested to compare performance. The final algorithm was tested with different input images to find if the annual line detection algorithm works best with images from a grayscale or an RGB camera.
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Reid, G. T. "Automatic moire topography." Thesis, University of Strathclyde, 1988. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.314722.
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Inglis, Iain McAllister. "Semi-automatic image processing with application to fungal hyphae." Thesis, University of Strathclyde, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.366773.
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Davila, Garcia Maria Luisa. "Image processing methods for automatic in-vitro morphology analysis." Thesis, University of Sheffield, 2018. http://etheses.whiterose.ac.uk/22501/.
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The study of male infertility has become a priority for biologists and researchers in the last decades as a consequence of the declining birth rates. This problem has also become a major public health with economic and psychosocial consequences. Analysis of human sperm cells, for instance, is widely used in investigations related to male infertility and assisted conception. Sperm samples are usually analysed by health professionals using microscope devices following a manual process to count and describe their morphology. Nevertheless, this practice is prone to errors and time consuming. This thesis proposes a novel framework based on image processing and machine learning methods to automate the analysis of sperm cells. The proposed method presented an average accuracy performance of 96.4% classify automatically sperm cells in three classes: normal, abnormal and non sperm cell. Performance results have been obtained in challenging conditions: presence of uneven illumination, unwanted noise and blurring caused by the focus drift and occlusion of objects as a result of the overlapping of sperm cells, among others. The object of interest, sperm cells, captured in the images used in this research did not receive any staining or fixation treatment prior to their capture. A novel and robust methodology based on deep neural learning is developed as part of the automatic feature selection prior to the classification. Also, video and image database of sperm samples was produced at the Andrology laboratory of the University of Sheffield as part of this work. The database was used to validate the proposed framework for the segmentation and classification of in-vitro cells.
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Prager, Richard William. "Parallel processing networks for automatic speech recognition." Thesis, University of Cambridge, 1987. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.238443.
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Yu, Hongliang. "Automatic Rigid and Deformable Medical Image Registration." Link to electronic thesis, 2005. http://www.wpi.edu/Pubs/ETD/Available/etd-050905-100341/.
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Jay, Emmanuel. "An architecture towards automatic image based modelling." Thesis, University of Sussex, 2002. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.250168.
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Ha, Jin-cheol. "Real-time visual tracking using image processing and filtering methods." Diss., Atlanta, Ga. : Georgia Institute of Technology, 2008. http://hdl.handle.net/1853/28177.
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Thesis (M. S.)--Aerospace Engineering, Georgia Institute of Technology, 2008.Committee Chair: Eric N. Johnson; Committee Co-Chair: Allen R. Tannenbaum; Committee Member: Anthony J. Calise; Committee Member: Eric Feron; Committee Member: Patricio A. Vela.
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Adeboye, Taiyelolu. "Robot Goalkeeper : A robotic goalkeeper based on machine vision and motor control." Thesis, Högskolan i Gävle, Avdelningen för elektronik, matematik och naturvetenskap, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:hig:diva-27561.
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This report shows a robust and efficient implementation of a speed-optimized algorithm for object recognition, 3D real world location and tracking in real time. It details a design that was focused on detecting and following objects in flight as applied to a football in motion. An overall goal of the design was to develop a system capable of recognizing an object and its present and near future location while also actuating a robotic arm in response to the motion of the ball in flight. The implementation made use of image processing functions in C++, NVIDIA Jetson TX1, Sterolabs’ ZED stereoscopic camera setup in connection to an embedded system controller for the robot arm. The image processing was done with a textured background and the 3D location coordinates were applied to the correction of a Kalman filter model that was used for estimating and predicting the ball location. A capture and processing speed of 59.4 frames per second was obtained with good accuracy in depth detection while the ball was well tracked in the tests carried out.
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Nassif, Samer Chaker. "Cooperative windowing for real-time visual tracking." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1997. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp03/NQ30107.pdf.
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O'Malley, Patrick D. "Human activity tracking for wide-area surveillance." [Gainesville, Fla.] : University of Florida, 2002. http://purl.fcla.edu/fcla/etd/UFE1000150.
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Thesis (M.S.)--University of Florida, 2002.Title from title page of source document. Document formatted into pages; contains vi, 46 p.; also contains graphics. Includes vita. Includes bibliographical references.
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Petkova, Desislava I. "Cluster-based relevance models for automatic image annotation /." Connect to online version, 2005. http://ada.mtholyoke.edu/setr/websrc/pdfs/www/2005/124.pdf.
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Eliassen, Lars Moland. "Automatic Fish Classification : Using Image Processing and Case-Based Reasoning." Thesis, Norges teknisk-naturvitenskapelige universitet, Institutt for datateknikk og informasjonsvitenskap, 2012. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-18457.
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Counting and classifying fish moving upstream in rivers to spawn is a useful way of monitoring the population of different species. Today, there exist some commercial solutions, along with some research that addresses the area. Case-based reasoning is a process that can be used to solve new problems based on previous problems. This thesis studies the possibilities of combining image processing techniques and case-based reasoning to classify species of fish which are similar to each other in both shape, size and color. Methods for image preprocessing are discussed, and tested. Methods for feature extraction and a case-based reasoning prototype are proposed, implemented and tested with promising results.
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Jiang, Yuchong. "Automatic assessment of skeletal maturity by digital image processing methods." Thesis, University of Liverpool, 1993. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.333501.
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Morales, Martínez Sandra. "Fundus characterization for automatic disease screening through retinal image processing." Doctoral thesis, Editorial Universitat Politècnica de València, 2015. http://hdl.handle.net/10251/53933.
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[EN] The World Health Organization estimates that in 2010 there were 285 million people visually impaired in the world. It is calculated that the 80\% of these cases are preventable or treatable. In addition, aging population and chronic disease increase are two factors that predict a higher number of blindness cases in the future. Hypertension, diabetic retinopathy (DR), age-related macular degeneration (AMD) and glaucoma are the most common pathologies in the current society that provoke retinal damage and can be directly related to blindness and vision loss. The early diagnosis of these diseases allows, through appropriate treatment, to reduce costs generated when they are in advanced states and may become chronic. This fact justifies screening campaigns. However, a screening campaign requires a heavy workload for trained experts in the analysis of anomalous patterns of each disease, which in addition to the increase of population at risk, makes these campaigns economically unfeasible. Therefore, the need of automatic screening system developments is highlighted.
The final goal of this thesis is the implementation of novel methods that allow the analysis and processing of fundus images to implement an automatic screening of four of the most important diseases that affect world population. In particular, the main objective of the thesis is to build up algorithms for the characterization of the retinal structures and the retina background in order to assist in the discrimination between a ``normal" and pathological retina.
Mathematical morphology along with other operators are used for the detection of the retinal vessels and the optic disk. The proposed methods work properly on databases with a large degree of variability. Not only have the main structures been segmented, but significant features have also been extracted from them to be used in a computer aided diagnosis software for hypertensive risk determination. The texture of the retina background is also analyzed in this work by means of local binary patterns with the aim of identifying DR and AMD and avoiding the need of segmentation of the characteristic retinal lesions of each disease. The results are promising above all for AMD diagnosis.[ES] La Organización Mundial de la Salud estima que en 2010 había 285 millones de personas con alguna discapacidad visual en el mundo. Se calcula que el 80\% de estos casos son evitables o tratables. Además, el envejecimiento de la población y el aumento de las enfermedades crónicas son dos factores que hacen prever un número todavía mayor de casos de ceguera en el futuro. La hipertensión, la retinopatía diabética (RD), la degeneración macular asociada a la edad (DMAE) y el glaucoma son las enfermedades más comunes que provocan daños en la retina y, por tanto, están directamente relacionadas con la ceguera y con la pérdida de visión. El diagnóstico de estas enfermedades en estadios tempranos permite, mediante el tratamiento adecuado, reducir los costes que generan en estados ya avanzados y que en la mayoría de los casos acaban convirtiéndose en crónicas, lo que justifica la realización de campañas de cribado. Sin embargo, una campaña de cribado exige una gran carga de trabajo de personal experto entrenado en el análisis de los patrones anómalos propios de cada enfermedad, lo que sumado al aumento de la población de riesgo, hace que estas campañas sean inviables económicamente. Por lo tanto, se evidencia la necesidad del desarrollo de sistemas de cribado automáticos. El objetivo final del presente trabajo es la implementación de métodos novedosos de análisis de imágenes de fondo de ojo para usarlos en un sistema de cribado de cuatro de las enfermedades más importantes que afectan a la población actual. En concreto, el objetivo principal de la tesis es el desarrollo de algoritmos para la caracterización de las estructuras y del fondo retiniano, los cuales servirán de ayuda para discriminar una retina ``normal" de otra patológica. Para la detección de los vasos retinianos y del disco óptico, se ha usado morfología matemática además de otros operadores. Se ha demostrado que los métodos propuestos para este fin funcionan adecuadamente en bases de datos con un alto grado de variabilidad. No sólo se han segmentado las principales estructuras retinianas, sino que, además, se han extraído sus características más significativas para determinar el riesgo hipertensivo. En este trabajo, también se han analizado las texturas presentes en el fondo de la retina por medio de la teoría de los patrones binarios locales con el objetivo de identificar la RD y la DMAE a la vez que se evita la necesidad de la segmentación de las lesiones específicas de cada enfermedad. Los resultados son prometedores, sobre todo, para la detección de la DMAE.
[CAT] L'Organització Mundial de la Salut estima que en 2010 havia 285 milions de persones amb alguna discapacitat visual en el món. Es calcula que el 80\% d'aquests casos són evitables o tractables. A més, l'envelliment de la població i l'augment de les malalties cròniques són dos factors que fan preveure un número encara major de casos de ceguera en el futur. La hipertensió, la retinopatia diabètica (RD), la degeneració macular associada a l'edat (DMAE) i el glaucoma són les malalties més comuns que provoquen danys en la retina i, per tant, estan directament relacionades amb la ceguera i amb la pèrdua de visió. El diagnòstic d'aquestes malalties en estadis primerencs permet, per mitjà del tractament adequat, reduir els costos que generen en estats ja avançats i que en la majoria dels casos acaben convertint-se en cròniques, la qual cosa justifica la realització de campanyes de garbellament. No obstant això, una campanya de garbellament exigix una gran càrrega de treball de personal expert entrenat en l'anàlisi dels patrons anòmals propis de cada malaltia, que si es suma a l'augment de la població de risc, fa que aquestes campanyes siguen inviables econòmicament. Per tant, s'evidencia la necessitat del desenrotllament de sistemes de garbellament automàtics. L'objectiu final del present treball és la implementació de mètodes nous d'anàlisi d'imatges de fons d'ull per a usar-los en un sistema de garbellament de quatre de les malalties més importants que afecten la població actual. En concret, l'objectiu principal de la tesi és el desenvolupament d'algoritmes per a la caracterització de les estructures i del fons retinià, els quals serviran d'ajuda per a discriminar una retina ``normal" d'una altra patològica. Per a la detecció dels vasos retinians i del disc òptic, s'ha usat morfologia matemàtica a més d'altres operadors. S'ha demostrat que els mètodes proposats per a aquest fi funcionen adequadament en bases de dades amb un alt grau de variabilitat. No sols s'han segmentat les principals estructures retinianes, sinó que, a més, s'han extret les seues característiques més significatives per a determinar el risc hipertensiu. En aquest treball, també s'han analitzat les textures presents en el fons de la retina per mitjà de la teoria dels patrons binaris locals amb l'objectiu d'identificar la RD i la DMAE al mateix temps que s'evita la necessitat de la segmentació de les lesions específiques de cada malaltia. Els resultats són prometedors, sobretot, per a la detecció de la DMAE.
Morales Martínez, S. (2015). Fundus characterization for automatic disease screening through retinal image processing [Tesis doctoral]. Editorial Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/53933
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Ostergaard, Lindsey Eubank. "Automatic Detection and Characterization of Parasite Eggs by Image Processing." Thesis, Virginia Tech, 2013. http://hdl.handle.net/10919/51856.
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The accurate identification of parasites allows for the quick diagnosis and treatment of infections. Current state-of-the-art identification techniques require a trained technician to examine prepared specimens by microscope or other molecular methods. In an effort to automate the process and better facilitate the field identification of parasites, approaches are developed to utilize LabVIEW and MATLAB, which are commercially available image processing software packages, for parasite egg identification. The goal of this project is to investigate different image processing techniques and descriptors for the detection and characterization of the following parasite eggs: Ascaris lumbricoides, Taenia sp., and Paragonimus westermani. One manual approach and four automated approaches are used to locate the parasite eggs and gather parasite characterization data. The manual approach uses manual measurements of the parasite eggs within the digital images. The four automated approaches are LabVIEW Vision Assistant scripts, MATLAB separation code, MATLAB cross-section grayscale analysis, and MATLAB edge signature analysis. Forty-four separate measurements were analyzed through the four different approaches. Two types of statistical tests, single factor global Analysis of Variance (ANOVA) test and Multiple Comparison tests, are used to demonstrate that parasite eggs can be differentiated. Thirty-six of the measurements proved to be statistically significant in the differentiation of at least two of the parasite egg types. Of the thirty-six measurements, seven proved to be statistically significant in the differentiation of all three parasite egg types. These results have shown that it is feasible to develop an automated parasite egg detection and identification algorithm through image processing. The automated image processing techniques have proven successful at differentiating parasite eggs from background material. This initial research will be the foundation for future software structure, image processing techniques, and measurements that should be used for automated parasite egg detection.Master of Science
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Irwin, Philip D. S. "Real-time processing techniques for infra-red image understanding." Thesis, Queen's University Belfast, 1989. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.335976.
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McGraw, Tim E. "Neuronal fiber tracking in DT-MRI." [Gainesville, Fla.] : University of Florida, 2002. http://purl.fcla.edu/fcla/etd/UFE0000573.
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Atiquzzaman, M. "Algorithms and architectures for automatic traffic analysis." Thesis, University of Manchester, 1986. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.378141.
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Walsh, Dane A. "Automatic detection of image orientation using Support Vector Machines." Thesis, Stellenbosch : Stellenbosch University, 2002. http://hdl.handle.net/10019.1/52717.
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Thesis (MSc)--University of Stellenbosch, 2002.ENGLISH ABSTRACT: In this thesis, we present a technique for the automatic detection of image orientation using Support Vector Machines (SVMs). SVMs are able to handle feature spaces of high dimension and automatically choose the most discriminative features for classification. We investigate the use of various kernels, including heavy tailed RBF kernels. We compare the classification performance of SVMs with the performance of multilayer perceptrons and a Bayesian classifier. Our results show that SVMs out perform both of these methods in the classification of individual images. We also implement an application for the classification of film rolls in a photographic workflow environment with 100% classification accuracy.
AFRIKAANSE OPSOMMING: In hierdie tesis, gebruik ons 'n tegniek vir die automatiese klassifisering van beeldoriëntasie deur middel van Support Vector Machines (SVM's). SVM's kan kenmerkruimtes van 'n hoë dimensie hanteer en kan automaties die mees belangrike kenmerke vir klassifikasie kies. Ons vors die gebruik van verskeie kerne, insluitende RBF-kerne, na. Ons vergelyk die klassifiseringsresultate van SVM's met die van multilaagperseptrone en 'n Bayes-klassifiseerder. Ons bewys dat SVM's beter resultate gee as beide van hierdie metodes vir die klassifikasie van individuele beelde. Ons implementeer ook a toepassing vir die klassifisering van rolle film in a fotografiese werkvloei-omgewing met 100% klassifikasie akuraatheid.
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Floyd, Beatrice K. "Vision-Based Techniques for Cognitive and Motor Skill Assessments." Case Western Reserve University School of Graduate Studies / OhioLINK, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=case1338824242.
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Johnson, Abioseh Saeley. "Automatic number-plate recognition : an application of computer vision technology to automatic vehicle identification." Thesis, University of Bristol, 1990. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.300053.
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