Submitted by Maike Costa (maiksebas@gmail.com) on 2016-05-10T12:46:44Z No. of bitstreams: 1 arquivo total.pdf: 3109388 bytes, checksum: 647810f9fb25d144a271d5f256240096 (MD5) / Made available in DSpace on 2016-05-10T12:46:44Z (GMT). No. of bitstreams: 1 arquivo total.pdf: 3109388 bytes, checksum: 647810f9fb25d144a271d5f256240096 (MD5) Previous issue date: 2014-08-01 / Conselho Nacional de Pesquisa e Desenvolvimento Científico e Tecnológico - CNPq / This work presents two methods based on digital image analysis, diffuse reflectance spectroscopy in the visible espectral range and multivariate analysis to classify seeds castor with respect to the type of cultivar and genotype. For this purpose, two groups of seeds commonly used in Brazilian plantations were evaluated: BRS Nordestina e BRS Paraguaçu (group I), BRS Energia cultivar and CNPA 2009-7 (group II) The diffuse reflectance spectra were recorded in the region 400-800 nm obtained by a spectrophotometer VIS-NIR. The Images of these two groups were registered from a webcam and frequency distribution of color indixes in the red-green-blue channels, hue, saturation, intensity and grayscale was obtained. The discriminant analysis by partial least squares (PLS-DA) and linear discriminant analysis were applied separately for each group of seed. The best results were obtained using the PLS-DA model correctly classified samples to visible 96.2% and 92.5% of test samples for the group I and II, respectively. For digital images PLS-DA also achieved the best result hitting 98.7% and 100% for group I and II, respectively. The methods here proposed based on digital image analysis and diffuse reflectance spectroscopy in the visible range has advantages for not using reagents, are fast, inexpensive and are promising in the classification of castor alternatives, according to the type of cultivar and genotypes / Este trabalho apresenta dois métodos baseados em análise de imagens digitais, espectroscopia de reflectância difusa no vísivel e análise multivariada para classificação de sementes de mamona com respeito ao tipo de cultivar e genótipo. Para este propósito, dois grupos de sementes comumente empregadas nas plantações brasileiras foram avaliados: cultivares BRS Nordestina e BRS Paraguaçu (grupo I), cultivar BRS Energia e o genótipo CNPA 2009-7 (grupo II). Os espectros de reflectância difusa foram registrados na região de 400 a 800 nm obtidos através de um espectrofotômetro VIS-NIR. Imagens destes dois grupos foram registradas a partir de uma webcam e a distribuição de frequência em níveis de cores nos canais vermelhoverde- azul, matiz, saturação, intensidade e tons de cinza foi obtida. A Análise Discriminante pelos mínimos quadrados parciais (PLS-DA) e Análise discriminante linear (LDA) foram aplicadas separadamente para cada grupo de semente. Para os espectros do visível os melhores resultados foram obtidos usando o modelo PLS-DA, classificando corretamente 96,2% e 92,5% das amostras de teste para o grupo I e II, respectivamente. Para as imagens digitais o PLS-DA também alcançou o melhor resultado acertando 98,7% e 100% para o grupo I e II, respectivamente. Os métodos baseados em imagens digitais e espectroscopia de reflectância difusa no visível propostos tem vantagens por não utilizar reagentes, são rápidos, não-destrutivos, baixo custo e são alternativas promissoras na classificação de sementes de mamona, de acordo com o tipo de cultivar e genótipos.

This work presents a computational tool to support the evaluation of displacement and strain fields by using Digital Image Correlation (DIC) techniques. Two images, referring to different stages of the problem, are analyzed in order to measure these fields. As most often experimental tests are on small scale, the required tools may interfere with the analisys results. Therefore, non-destructive techniques as the DIC can be used as supporting tools for these tests. Besides, DIC is also used in situations when the access doesn’t allow the proper positioning of the tool. The subset DIC algorithm is applied, which consists in splitting the images into subregions, in which the displacements and strains are evaluated. In order to obtain the unknown fields over the whole image, the results from each subregion are interpolated. Then, tests are performed to validate the proposed methodology through four examples, by comparing the results with analytical, numerical or experimental ones, presented in the literature, in which a good level of agreement is observed. Furthermore, two numerical examples are simulated, concerning a triaxial compression test and a diametral compression test. In both cases, the displacement values are obtained with minor errors. / CAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / Este trabalho apresenta uma ferramenta computacional para auxiliar na análise de campos de deslocamentos e deformações através de técnicas de correlação de imagens digitais (DIC) e consiste na avaliação de duas imagens em estágios diferentes de um determinado problema para a obtenção desses campos. Como na maioria das vezes os ensaios experimentais são realizados em modelos reduzidos, as instrumentações normalmente utilizadas podem afetar os resultados da análise. Então, técnicas não destrutivas como a DIC podem ser utilizadas como ferramentas de apoio a esses ensaios. Além disso, a DIC também é utilizada na análise de elementos com difícil acesso para a colocação da instrumentação convencional. Neste trabalho utiliza-se a técnica Subset DIC Algorithm que divide as imagens em várias sub-regiões e analisa os deslocamentos e as deformações para cada sub-região. Para a obtenção do campo de deslocamentos e deformações da imagem faz-se uma interpolação dos resultados obtidos em cada sub-região. Em seguida, são realizados testes para a validação da metodologia proposta através de quatro exemplos, inclusive fazendo comparações dos resultados com respostas analíticas, numéricas ou experimentais encontradas na literatura, em que, obtiveram-se respostas satisfatórias na obtenção dos campos de deslocamentos e deformações. Também são realizados dois estudos de caso sendo um sobre o ensaio de compressão triaxial e o outro sobre o ensaio de compressão diametral. Em ambos os estudos de caso é possível obter os campos de deslocamentos com erros satisfatórios.

No description available.

Approved for public release; distribution in unlimited. / Traditionally, digital imaging systems rely on the use of dedicated photodetectors to capture specific wavelengths in the visible spectrum. These photodetectors, which are commonly made of silicon, are arranged as arrays to capture the red, green and blue wavelengths. The signal captured by the individual photodetectors must then be interpolated and integrated to obtain the closest color match and the finest possible resolution with reference to the actual object. The use of spatially separated detectors to sense primary colors reduces the resolution by a factor of three compared to black and white imaging. The FOVEON detector technology greatly improves the color and resolution of the image through its vertically arranged, triple well photodetector. This is achieved by exploiting the variation of absorption coefficient of silicon with wavelength in the visible spectrum. Hence, in a silicon detector, the shorter wavelength (e.g. blue) would be mainly absorbed at a shallow depth. A longer wavelength (e.g. red) would penetrate the material deeper than the shorter wavelengths and be primarily absorbed at a greater depth. By producing a layered silicon detector, all three primary colour wavelengths of red, green and blue can be captured simultaneously. This thesis aims to study the FOVEON camera's ability to image light from the near Infrared (NIR) to the Ultra-Violet (UV) range of the electromagnetic spectrum. The imaged obtained using a set of bandpass filters show that the camera has response both in the UV as well as NIR regions. / Major, Singapore Armed Forces

En imagerie numérique, les approches «problèmes inverses» régularisées reconstruisent une information d'intérêt à partir de mesures et d'un modèle de formation d'image. Le problème d'inversion étant mal posé, mal conditionné et le modèle de formation d'image utilisé peu contraint, il est nécessaire d'introduire des a priori afin de restreindre l'ambiguïté de l'inversion. Ceci permet de guider la reconstruction vers une solution satisfaisante. Les travaux de cette thèse ont porté sur le développement d'algorithmes de reconstruction d'hologrammes numériques, basés sur des méthodes d'optimisation en grande dimension (lisse ou non-lisse). Ce cadre général a permis de proposer différentes approches adaptées aux problématiques posées par cette technique d'imagerie non conventionnelle : la super­-résolution, la reconstruction hors du champ du capteur, l'holographie «couleur» et enfin la reconstruction quantitative d'objets de phase (c.a.d. transparents). Dans ce dernier cas, le problème de reconstruction consiste à estimer la transmittance complexe 2D des objets ayant absorbé et/ou déphasé l'onde d'éclairement lors de l'enregistrement de l'hologramme. Les méthodes proposées sont validées à l'aide de simulations numériques puis appliquées sur des données expérimentales issues de l'imagerie sans lentille ou de la microscopie holographique en ligne (imagerie cohérente en transmission, avec un objectif de microscope). Les applications vont de la reconstruction de mires de résolution opaques à la reconstruction d'objets biologiques (bactéries), en passant par la reconstruction de gouttelettes d'éther en évaporation dans le cadre d'une étude de la turbulence en mécanique des fluides. / In Digital Imaging, the regularized inverse problems methods reconstruct particular information from measurements and an image formation model. With an inverse problem that is ill-posed and ill­conditioned, and with the used image formation mode! having few constraints, it is necessary to introduce a priori conditions in order to restrict ambiguity for the inversion. This allows us to guide the reconstruction towards a satisfying solution. The works of the following thesis delve into the development of reconstruction algorithms of digital holograms based on large-scale optimization methods (smooth and non-smooth). This general framework allowed us to propose different approaches adapted to the challenges found with this unconventional imaging technique: the super-resolution, reconstruction outside the sensor's field, the color holography and finally, the quantitative reconstruction of phase abjects (i.e. transparent). For this last case, the reconstruction problem consists of estimating the complex 2D transmittance of abjects having absorbed and/or dephased the light wave during the recording of the hologram. The proposed methods are validated with the help of numerical simulations that are then applied on experimental data taken from the lensless imaging or from the in-line holographie microscopy (coherent imaging in transmission, with a microscope abject glass). The applications range from the reconstruction of opaque resolution sights, to the reconstruction of biological objects (bacteria), passing through the reconstruction of evaporating ether droplets from a perspective of turbulence study in fluid mechanics.

No description available.

Rheumatoid Arthritis (RA) is a disease in which the body has "turned on itself", with its immune system attacking mobility. In RA, an immune mechanism attacks and destroys the joints and limits mobility, in some circumstances to the point of needing replacement of joints. The aim of this research is the development of a less costly, widely accessible, passive sensing technology that provides a quantitative assessment of RA and that monitors the therapeutic effectiveness on joint-debilitating diseases. The proposed solution relies on a quantitative evaluation of human gestures. Such a quantitative assessment supports the comparison between the motion capabilities of a patient and that of a healthy person, using a kinematic model of the human skeleton. Criteria for the classification of severity were established, and tables were generated to classify the levels of severity as a function of the measurements extracted from processed videos of a subject performing predefined movements. This research project, while contributing a new tool to the process of classification of RA level of severity, opens the way for using widely accessible digital imaging for diagnosing and monitoring the evolution of the illness. Replacing MRI or HRUS with a cheaper and more accessible technology would have a major impact on health care services. From the clinical point of view, the proposed techniques based on digital images processing combined with a monitoring approach based on infrared images that was previously developed may provide a utility of care for patients with RA, as well as an alternative and automated approach for early detection of RA and active inflammation at a critical time.

Η παρούσα διπλωματική εργασία, πραγματεύεται την εύρεση της κυματομορφής της μεταβολής της φωτεινότητας φωτονίων που διέρχονται από το χέρι ανθρώπου και δίνουν πληροφορία για την αρτηριακή πίεση και κατ’ επέκταση τον υπολογισμό του καρδιακού ρυθμού ενός ατόμου με τη χρήση τεχνικών επεξεργασίας εικόνας. Χρησιμοποιώντας μια σειρά από διόδους εκπομπής, στο ορατό και υπέρυθρο φάσμα, κατευθύνουμε το φως προς ένα δίκτυο ιστών όπου αυτό είναι λεπτό και το διαπερνά (δάκτυλο, λοβίο αυτιού κλπ). Στη συνέχεια, μέσω μιας βιντεοκάμερας παίρνουμε τα υπό εξέταση δεδομένα. Συγκρίνοντας την απορρόφηση του φωτός στις διαδοχικές εικόνες και ύστερα από κατάλληλη επεξεργασία των εικόνων με τη βοήθεια του Matlab οδηγούμαστε στην εύρεση του καρδιακού ρυθμού. / The present thesis deals with the determination of the waveform that depicts the fluctuation of the brightness of photons which pass through the hand of a person and provides information for the arterial pressure. Exploiting the results through digital image processing techniques, subject’s cardiac rhythm can be conclusively calculated. Using a series of diodes emitting in the visible spectrum along with a second series of diodes emitting in the infrared spectrum, we direct their light to a part of the human tissue which is thin (finger, earlobe etc) and can be easily penetrated. Afterwards via a CCD video camera we capture picture data of the light that is not absorbed. Cardiac rhythm can be calculated by comparing the absorption of light in successive pictures processed by digital imaging processing tools of Matlab.

Rheumatoid Arthritis (RA) is a disease in which the body has "turned on itself", with its immune system attacking mobility. In RA, an immune mechanism attacks and destroys the joints and limits mobility, in some circumstances to the point of needing replacement of joints. The aim of this research is the development of a less costly, widely accessible, passive sensing technology that provides a quantitative assessment of RA and that monitors the therapeutic effectiveness on joint-debilitating diseases. The proposed solution relies on a quantitative evaluation of human gestures. Such a quantitative assessment supports the comparison between the motion capabilities of a patient and that of a healthy person, using a kinematic model of the human skeleton. Criteria for the classification of severity were established, and tables were generated to classify the levels of severity as a function of the measurements extracted from processed videos of a subject performing predefined movements. This research project, while contributing a new tool to the process of classification of RA level of severity, opens the way for using widely accessible digital imaging for diagnosing and monitoring the evolution of the illness. Replacing MRI or HRUS with a cheaper and more accessible technology would have a major impact on health care services. From the clinical point of view, the proposed techniques based on digital images processing combined with a monitoring approach based on infrared images that was previously developed may provide a utility of care for patients with RA, as well as an alternative and automated approach for early detection of RA and active inflammation at a critical time.

Organic semiconductor technology has gained attention in both the sensor and display markets due to its low cost and simple fabrication techniques. The ability to fabricate organic semiconductor devices such as photodetectors and transistors on a flexible, lightweight substrate makes them less fragile and ideal candidates for portable large-area imaging applications. The use of organic semiconductor technology in large-area medical imaging can bring about a new generation of flexible and lightweight indirect X-ray imagers. These imagers are immune to mechanical shock and should be ideal for portable intraoral X-ray radiology. In order to realize these organic flexible imagers and their use in large-area medical imaging, many challenges associated with the device performance and fabrication need to be overcome. Among these challenges, one of the greatest is to improve the dark current performance of the organic semiconductor photodetectors (key for imager performance) with a high-photo to-dark current ratio. Low dark current is needed to improve the sensitivity of the imager, whereas a large photo-to-dark current ratio reduces noise in the extracted image. Numerous techniques have been reported to improve the dark current performance in vertical organic photodetector design; however, lateral photodetectors still lack research attention. This thesis presents a lateral multilayer photodetector design and a simplified technique to improve the dark current performance of lateral organic semiconductor photodetectors. Our technique allows us to apply a large bias voltage while maintaining a low dark current, high photo-to-dark current ratio, and improves detector speed; thus, the overall sensitivity of the detector is improved. We further show the integration of an organic photodetector with an organic backplane readout circuit to form a flexible large-area imager. This imager can be used for large-area digital imaging applications such as in medical radiology.