When a Time-of-Flight (ToF) depth camera is used to monitor a region of interest, it has to be mounted correctly and have information regarding its position. Manual configuration currently require managing captured 3D ToF data in a 2D environment, which limits the user and might give rise to errors due to misinterpretation of the data. This thesis investigates if a real time 3D reconstruction mesh from a Microsoft HoloLens can be used as a target for point cloud registration using the ToF data, thus configuring the camera autonomously. Three registration algorithms, Fast Global Registration (FGR), Joint Registration Multiple Point Clouds (JR-MPC) and Prerejective RANSAC, were evaluated for this purpose. It was concluded that despite using different sensors it is possible to perform accurate registration. Also, it was shown that the registration can be done accurately within a reasonable time, compared with the inherent time to perform 3D reconstruction on the Hololens. All algorithms could solve the problem, but it was concluded that FGR provided the most satisfying results, though requiring several constraints on the data.

Submitted by Samuel Almeida Santos de Oliveira (panodepitanga@gmail.com) on 2018-04-24T20:34:06Z No. of bitstreams: 1 Samuel Almeida Santos de Oliveira Dissertação.pdf: 4334443 bytes, checksum: 1bb38a41c0f44ddc309396cb70cdafa0 (MD5) / Rejected by Maria Lucia Martins Frederico null (mlucia@fca.unesp.br), reason: Prezado !!! Colocar em seu arquivo Agradecimento ao órgão financiador uma vez que referiu ter recebido (CAPES) on 2018-04-25T12:18:33Z (GMT) / Submitted by Samuel Almeida Santos de Oliveira (panodepitanga@gmail.com) on 2018-04-26T13:19:23Z No. of bitstreams: 1 Dissertação Samuel Repositório.pdf: 4332343 bytes, checksum: 48147e283548133e9e25c6aaced6ab1e (MD5) / Approved for entry into archive by Maria Lucia Martins Frederico null (mlucia@fca.unesp.br) on 2018-04-26T13:46:38Z (GMT) No. of bitstreams: 1 oliveira_sas_me_botfca.pdf: 4228224 bytes, checksum: 0935cecf686a1a0e092949fa095ef242 (MD5) / Made available in DSpace on 2018-04-26T13:46:38Z (GMT). No. of bitstreams: 1 oliveira_sas_me_botfca.pdf: 4228224 bytes, checksum: 0935cecf686a1a0e092949fa095ef242 (MD5) Previous issue date: 2018-02-28 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) / A atividade agrícola tem importância significativa na economia, justificando diversas pesquisas que busquem a aquisição de informações e desenvolvimento de tecnologias para que os processos envolvidos sejam mais eficientes. A topografia, geodésia e geoprocessamento têm sido utilizados de forma crescente e de diversas formas, tanto para monitoramento, quanto para planejamento na gestão agronômica e dos recursos naturais. O presente trabalho foi realizado na Fazenda Experimental Lageado, em Botucatu-SP e teve por objetivo aferir cartas do IGC e IBGE em comparação com equipamentos de alta precisão, nas quais foram confeccionadas linhas de perfis altimétricos e interpolação dos valores de altimetria. A geoestatística foi utilizada para uma interpolação com predição de erros, na qual os semi-variogramas e a validação cruzada permitiram analisar a correlação espacial e variância dos dados estimados. Como resultados foram obtidos mapas de altimetria, declividade e respectivos residuais altimétricos absolutos para a mensuração da confiabilidade de cartas na classificação de relevo, como também, o uso de cartas para traçado de limites de confrontações naturais, como linhas de cumeada e grota. Pôde-se concluir que não é confiável utilizar as cartas para determinação de limites de confrontação natural como linhas de cumeadas e grotas para certificação de cadastro de registro de imóveis. / The agriculture has a significant importance in economy, demanding several researches that allow information acquisition and technology development aiming an enhancing of the processes involved. Land surveying, geodetic sciences and geoprocessing have been more applied, and in different ways for land monitoring, soil and nature resources management. The present essay was developed on the Experimental Farm Fazenda Experimental Lageado Botucatu – SP, Brazil and aimed an altimetry analysis of IGC and IBGE contour maps with accurate instruments as parameters, in which altimetry profile lines and interpolation of the altitude values were made. The kriging process was used, likewise the semi variogram model, and further the cross validation was made to achieve a known function for the altimetry value’s estimation, spatial correlation and value of variance. Digital elevation models, slope maps and the respective absolute altimetry residuals were made to measure the reliability of the IGC and IBGE contour maps as well as its usefulness for obtaining land topography and natural boundary from gardenbed or flume. It was concluded that the IGC and IBGE contour maps are not reliable for obtaining natural boundary from gardenbed or flume for certification of land registry in Brazil, although IGC contour maps were fine enough for morphometric analysis of small basins. IBGE contour maps as last option could be used for bigger basins analysis. / 1582108

Orientador: Antonio Maria Garcia Tommaselli / Banca: Daniel Rodrigues dos Santos / Banca: Mauricio Galo / Resumo: A utilização de imagens adquiridas por sensores CCD de médio formato, em plataformas aéreas, é uma alternativa para a redução de custos em projetos de aerolevantamento. Porém, alguns inconvenientes, como a pequena área de cobertura e a limitação às bandas do visível restringem algumas aplicações. Para resolver estes problemas podem ser usados vários sensores CCD simultaneamente, sendo necessária uma etapa posterior de fusão e registro destas imagens. Neste trabalho foram utilizados dois sistemas compostos por múltiplas câmaras, o Sistema de Aquisição e Pós-Processamento de Imagens Tomadas com Câmaras Digitais (SAAPI) e o Sistema de Câmaras Fuji. O sistema SAAPI permite diferentes configurações entre os sensores que o compõem, podendo estar nos modos duplooblíquo ou nadiral à área fotografada. A metodologia desenvolvida no trabalho trata duas questões envolvidas com a configuração de sistemas de múltiplas câmaras: o registro entre imagens IR e RGB e a fusão entre imagens RGB oblíquas, tendo como objetivo o aumento da resolução espectral e geométrica da imagem final produzida. Para isto são utilizados processos como a retificação e reamostragem de imagens. Estes, por sua vez, necessitam dos dados de calibração do sistema de câmaras, pois os parâmetros de orientação interior e exterior (POI e POE) são imprescindíveis para corrigir os efeitos das distorções nas imagens e o efeito da inclinação do sistema de câmaras. Experimentos realizados com imagens áreas, utilizando a metodologia proposta, demonstram que a discrepância nas coordenadas de pontos comuns às imagens registradas foi menor que 1 pixel. Este resultado é dependente da qualidade da calibração do sistema de câmaras / Abstract: The use of images acquired by medium format CCD sensors from aerial platforms, is a cost effective alternative for aerial surveying projects. However, some drawbacks, as small coverage area and limitation to the visible spectrum bands restrict some applications. To solve these problems multiple CCD sensors can be used simultaneously, requiring a later stage for registration and fusion of these images. In this study, two systems with multiple cameras, the System for Airborne Acquisition and Processing of Digital Images (SAAPI) and Fuji Camera System were used. The SAAPI system allows different configurations between the sensors that can be either double-oblique or nadir to the area photographed. The methodology developed in this study approached two issues involved with systems with multiple cameras: the registration between IR and RGB images and oblique RGB images fusion, aiming at increasing the geometric and spectral resolution of the final image to be produced. There were used processes such as rectification and images resampling. These processes require the previous camera and system calibration, because inner and exterior orientation parameters (IOP and EOP) are essential to correct the effects of distortions in the images and the effect of camera convergence within the system. Experiments performed with real terrestrial and aerial images using the proposed methodology, showed that the discrepancy in the coordinates of common points in the registered images were less than 1 pixel. This result is dependent on the quality of the system and camera calibration / Mestre

Thesis (MTech (Marketing))--Cape Peninsula University of Technology, 2017. / This thesis, through the lenses of technology acceptance theory, and considering the lack of online interactivity in service delivery, aimed at proposing a model of online business registration adoption for re-branding the government Department of Trade and Industry (DTI) Congo-Brazzaville. Task-Technology Fit (TTF) and Technology Acceptance Model (TAM) were the underpinning theories with which the study described the social phenomenon: online business registration adoption at DTI Congo-Brazzaville as branding tool. Arguably, in doctoral level, without underpinning theories, research conclusions look speculative. The use of theory to underpin this study was further motivated by its interpretative nature and the interplay between technical and non-technical factors which are involved in the process of technology adoption in service organisation. To come up with new engagement, and informed from successful implementation of DTI South Africa’s e-governance model, DTI Congo was used as case study; hence the country is known for being at the bottom of the pile when it comes to the ease of doing business ratings. Despite resultant benefits namely increased efficiency, effectiveness and improved service delivery that offer e-governance in making services nearer to citizens and easing the strenuous processes involved in manual operations, not all managers at the DTI Congo advocate the adoption of online business system. The problem is that insufficient advocacy of online business registration enforces the void of re-positioning the organisation vis-à-vis its internal customers (employees) as lean and innovative. The overall research question is: “how does the DTI Congo-Brazzaville intend to improve business registration using online business registration service as a branding tool”? The main objective therefore was to propose online service adoption re-branding and re-positioning DTI Congo-Brazzaville.

abstract: Hypoxia is a pathophysiological condition which results from lack of oxygen supply in tumors. The assessment of tumor hypoxia and its response to therapies can provide guidelines for optimization and personalization of therapeutic protocols for better treatment. Previous research has shown the difficulty in measuring hypoxia anatomically due to its heterogenous nature. This makes the study of hypoxia through various imaging modalities and mapping techniques crucial. The potential of hypoxia targeting T1 contrast agent GdDO3NI in generating hypoxia maps has been studied earlier. In this work, the similarities between hypoxia maps generated by MRI using GdDO3NI and pimonidazole based immunohistochemistry (IHC) in non-small cell lung carcinoma bearing mice have been studied. Six NCI-H1975 tumor-bearing mice were studied. All animal studies were approved by Arizona State University’s Institute of Animal Care and Use Committee (IACUC). Post co-injection of GdDO3NI and pimonidazole, T1 weighted 3D gradient echo MR images were acquired. For ex-vivo analysis of hypoxia, 30 μm thick tumor sections were obtained for each harvested tumor and were stained for pimonidazole and counter-stained with DAPI for nuclear staining. Pimonidazole (PIMO) is clinically used as a “gold standard” hypoxia marker. The key process involved stacking and iterative registration based on quality metric SSIM (Structural Similarity) Index of DAPI stained images of 5 consecutive tumor sections to produce a 3D volume stack of 150 μm thickness. Information from the 3D volume is combined to produce one final slide by averaging. The same registration transform was applied to stack the pimonidazole images which were previously thresholded to highlight hypoxic regions. The registered IHC stack was then co-registered with a single thresholded T1 weighted gradient echo MRI slice of the same location (~156 μm thick) using an elastic B-splines transform. The same transform was applied to achieve the co-registration of pimonidazole and MR percentage enhancement image. Image similarity index after the co-registration was found to be greater than 0.5 for 5 of the animals suggesting good correlation. R2 values were calculated for both hypoxic regions as well as tumor boundaries. All the tumors showed a high boundary correlation value of R2 greater than 0.8. Half of the animals showed high R2 values greater than 0.5 for hypoxic fractions. The RMSE values for the co-registration of all the animals were found to be low further suggesting better correspondence and validating the MR based hypoxia imaging. / Dissertation/Thesis / Masters Thesis Biomedical Engineering 2018

abstract: Image resolution limits the extent to which zooming enhances clarity, restricts the size digital photographs can be printed at, and, in the context of medical images, can prevent a diagnosis. Interpolation is the supplementing of known data with estimated values based on a function or model involving some or all of the known samples. The selection of the contributing data points and the specifics of how they are used to define the interpolated values influences how effectively the interpolation algorithm is able to estimate the underlying, continuous signal. The main contributions of this dissertation are three fold: 1) Reframing edge-directed interpolation of a single image as an intensity-based registration problem. 2) Providing an analytical framework for intensity-based registration using control grid constraints. 3) Quantitative assessment of the new, single-image enlargement algorithm based on analytical intensity-based registration. In addition to single image resizing, the new methods and analytical approaches were extended to address a wide range of applications including volumetric (multi-slice) image interpolation, video deinterlacing, motion detection, and atmospheric distortion correction. Overall, the new approaches generate results that more accurately reflect the underlying signals than less computationally demanding approaches and with lower processing requirements and fewer restrictions than methods with comparable accuracy. / Dissertation/Thesis / Ph.D. Bioengineering 2013

abstract: Multi-pulse particle tracking velocimetry (multi-pulse PTV) is a recently proposed flow measurement technique aiming to improve the performance of conventional PTV/ PIV. In this work, multi-pulse PTV is assessed based on PTV simulations in terms of spatial resolution, velocity measurement accuracy and the capability of acceleration measurement. The errors of locating particles, velocity measurement and acceleration measurement are analytically calculated and compared among quadruple-pulse, triple-pulse and dual-pulse PTV. The optimizations of triple-pulse and quadruple-pulse PTV are discussed, and criteria are developed to minimize the combined error in position, velocity and acceleration. Experimentally, the velocity and acceleration fields of a round impinging air jet are measured to test the triple-pulse technique. A high speed beam-splitting camera and a custom 8-pulsed laser system are utilized to achieve good timing flexibility and temporal resolution. A new method to correct the registration error between CCDs is also presented. Consequently, the velocity field shows good consistency between triple-pulse and dual-pulse measurements. The mean acceleration profile along the centerline of the jet is used as the ground truth for the verification of the triple-pulse PIV measurements of the acceleration fields. The instantaneous acceleration field of the jet is directly measured by triple-pulse PIV and presented. Accelerations up to 1,000 g's are measured in these experiments. / Dissertation/Thesis / M.S. Mechanical Engineering 2014

La présente thèse est consacrée au recalage et à la fusion d’images de façon dense et déformable via des méthodes d’optimisation discrète. La contribution majeure consiste en un principe de couplage entre recalage géométrique et iconique via l’utilisation de méthodes dites graphiques. Une telle formulation peut être obtenue à partir d’un Champ de Markov Aléatoire binaire et permet de résoudre les deux problèmes simultanément tout en imposant une cohérence à leurs solutions respectives. La méthodologie s’applique à la fusion de paires d’images (dans ses versions symétrique et asymétrique), ainsi qu’au recalage simultané de groupes d’images nécessaire à l’étude de populations. Les qualités principales de notre approche résident dans sa faible complexité algorithmique et sa versatilité. L’utilisation d’une formulation discrète assure une grande modularité concernant tant la mesure de similarité iconique que l’extraction et l’association de points d’intérêt. Les résultats prometteurs obtenus sur les bases de données de référence en flot optique et sur des données médicales tridimensionnelles démontrent tout le potentiel de notre méthodologie / This thesis is devoted to dense deformable image registration/fusion using discrete methods. The main contribution of the thesis is a principled registration framework coupling iconic/geometric information through graph-based techniques. Such a formulation is derived from a pair-wise MRF view-point and solves both problems simultaneously while imposing consistency on their respective solutions. The proposed framework was used to cope with pair-wise image fusion (symmetric and asymmetric variants are proposed) as well as group-wise registration for population modeling. The main qualities of our framework lie in its computational efficiency and versatility. The discrete nature of the formulation renders the framework modular in terms of iconic similarity measures as well as landmark extraction and association techniques. Promising results using a standard benchmark database in optical flow estimation and 3D medical data demonstrate the potentials of our methods.

L'objectif principal de cette thèse est la modélisation, compréhension et segmentation automatique de tumeurs diffuses et infiltrantes appelées Gliomes Diffus de Bas Grade. Deux approches exploitant des connaissances a priori de l'ordre spatial et anatomique ont été proposées. Dans un premier temps, la construction d'un atlas probabiliste qui illustre les positions préférentielles des tumeurs dans le cerveau est présentée. Cet atlas représente un excellent outil pour l'étude des mécanismes associés à la genèse des tumeurs et fournit des indications sur la position probable des tumeurs. Cette information est exploitée dans une méthode de segmentation basée sur des champs de Markov aléatoires, dans laquelle l'atlas guide la segmentation et caractérise la position préférentielle de la tumeur. Dans un second temps, nous présentons une méthode pour la segmentation de tumeur et le recalage avec absence de correspondances simultanés. Le recalage introduit des informations anatomiques qui améliorent les résultats de segmentation tandis que la détection progressive de la tumeur permet de surmonter l'absence de correspondances sans l'introduction d'un a priori. La méthode est modélisée comme un champ de Markov aléatoire hiérarchique et à base de grille sur laquelle les paramètres de segmentation et recalage sont estimés simultanément. Notre dernière contribution est une méthode d'échantillonnage adaptatif guidé par les incertitudes pour de tels modèles discrets. Ceci permet d'avoir une grande précision tout en maintenant la robustesse et rapidité de la méthode. Le potentiel des deux méthodes est démontré sur de grandes bases de données de gliomes diffus de bas grade hétérogènes. De par leur modularité, les méthodes proposées ne se limitent pas au contexte clinique présenté et pourraient facilement être adaptées à d'autres problèmes cliniques ou de vision par ordinateur. / The main objective of this thesis is the automatic modeling, understanding and segmentation of diffusively infiltrative tumors known as Diffuse Low-Grade Gliomas. Two approaches exploiting anatomical and spatial prior knowledge have been proposed. We first present the construction of a tumor specific probabilistic atlas describing the tumors' preferential locations in the brain. The proposed atlas constitutes an excellent tool for the study of the mechanisms behind the genesis of the tumors and provides strong spatial cues on where they are expected to appear. The latter characteristic is exploited in a Markov Random Field based segmentation method where the atlas guides the segmentation process as well as characterizes the tumor's preferential location. Second, we introduce a concurrent tumor segmentation and registration with missing correspondences method. The anatomical knowledge introduced by the registration process increases the segmentation quality, while progressively acknowledging the presence of the tumor ensures that the registration is not violated by the missing correspondences without the introduction of a bias. The method is designed as a hierarchical grid-based Markov Random Field model where the segmentation and registration parameters are estimated simultaneously on the grid's control point. The last contribution of this thesis is an uncertainty-driven adaptive sampling approach for such grid-based models in order to ensure precision and accuracy while maintaining robustness and computational efficiency. The potentials of both methods have been demonstrated on a large data-set of heterogeneous Diffuse Low-Grade Gliomas. The proposed methods go beyond the scope of the presented clinical context due to their strong modularity and could easily be adapted to other clinical or computer vision problems.

Alors que la perspective de la fusion d’images médicales capturées par des systèmes d’imageries de type différent est largement contemplée, la mise en pratique est toujours victime d’un obstacle théorique : la définition d’une mesure de similarité entre les images. Des efforts dans le domaine ont rencontrés un certain succès pour certains types d’images, cependant la définition d’un critère de similarité entre les images quelle que soit leur origine et un des plus gros défis en recalage d’images déformables. Dans cette thèse, nous avons décidé de développer une approche générique pour la comparaison de deux types de modalités donnés. Les récentes avancées en apprentissage statistique (Machine Learning) nous ont permis de développer des solutions innovantes pour la résolution de ce problème complexe. Pour appréhender le problème de la comparaison de données incommensurables, nous avons choisi de le regarder comme un problème de plongement de données : chacun des jeux de données est plongé dans un espace commun dans lequel les comparaisons sont possibles. A ces fins, nous avons exploré la projection d’un espace de données image sur l’espace de données lié à la seconde image et aussi la projection des deux espaces de données dans un troisième espace commun dans lequel les calculs sont conduits. Ceci a été entrepris grâce à l’étude des correspondances entre les images dans une base de données images pré-alignées. Dans la poursuite de ces buts, de nouvelles méthodes ont été développées que ce soit pour la régression d’images ou pour l’apprentissage de métrique multimodale. Les similarités apprises résultantes sont alors incorporées dans une méthode plus globale de recalage basée sur l’optimisation discrète qui diminue le besoin d’un critère différentiable pour la recherche de solution. Enfin nous explorons une méthode qui permet d’éviter le besoin d’une base de données pré-alignées en demandant seulement des données annotées (segmentations) par un spécialiste. De nombreuses expériences sont conduites sur deux bases de données complexes (Images d’IRM pré-alignées et Images TEP/Scanner) dans le but de justifier les directions prises par nos approches. / Even though the prospect of fusing images issued by different medical imagery systems is highly contemplated, the practical instantiation of it is subject to a theoretical hurdle: the definition of a similarity between images. Efforts in this field have proved successful for select pairs of images; however defining a suitable similarity between images regardless of their origin is one of the biggest challenges in deformable registration. In this thesis, we chose to develop generic approaches that allow the comparison of any two given modality. The recent advances in Machine Learning permitted us to provide innovative solutions to this very challenging problem. To tackle the problem of comparing incommensurable data we chose to view it as a data embedding problem where one embeds all the data in a common space in which comparison is possible. To this end, we explored the projection of one image space onto the image space of the other as well as the projection of both image spaces onto a common image space in which the comparison calculations are conducted. This was done by the study of the correspondences between image features in a pre-aligned dataset. In the pursuit of these goals, new methods for image regression as well as multi-modal metric learning methods were developed. The resulting learned similarities are then incorporated into a discrete optimization framework that mitigates the need for a differentiable criterion. Lastly we investigate on a new method that discards the constraint of a database of images that are pre-aligned, only requiring data annotated (segmented) by a physician. Experiments are conducted on two challenging medical images data-sets (Pre-Aligned MRI images and PET/CT images) to justify the benefits of our approach.