991 resultados para Illumination conditions
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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The aim of this study was to test the influence of different degrees of additional illumination on visual caries detection using the International Caries Detection and Assessment System (ICDAS). Two calibrated examiners assessed 139 occlusal surfaces of extracted permanent molars using a standard operation lamp with or without an additional headlamp providing three default brightness intensities. Histology served as the gold standard. Pooled data showed no differences in sensitivities. Specificities were not influenced by additional light. The area under the curve for the Marthaler classification D3 threshold was significantly lower when an additional strong headlamp was used (0.59 compared to 0.69-0.72 when reduced illumination intensities were used). One of the two examiners also had a significantly lower sensitivity for the D1 threshold when an additional headlamp was used. The use of additional white light led to a reduced detection of dentine lesions.
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We develop a method for obtaining 3D polarimetric integral images from elemental images recorded in low light illumination conditions. Since photon-counting images are very sparse, calculation of the Stokes parameters and the degree of polarization should be handled carefully. In our approach, polarimetric 3D integral images are generated using the Maximum Likelihood Estimation and subsequently reconstructed by means of a Total Variation Denoising filter. In this way, polarimetric results are comparable to those obtained in conventional illumination conditions. We also show that polarimetric information retrieved from photon starved images can be used in 3D object recognition problems. To the best of our knowledge, this is the first report on 3D polarimetric photon counting integral imaging.
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Humans distinguish materials such as metal, plastic, and paper effortlessly at a glance. Traditional computer vision systems cannot solve this problem at all. Recognizing surface reflectance properties from a single photograph is difficult because the observed image depends heavily on the amount of light incident from every direction. A mirrored sphere, for example, produces a different image in every environment. To make matters worse, two surfaces with different reflectance properties could produce identical images. The mirrored sphere simply reflects its surroundings, so in the right artificial setting, it could mimic the appearance of a matte ping-pong ball. Yet, humans possess an intuitive sense of what materials typically "look like" in the real world. This thesis develops computational algorithms with a similar ability to recognize reflectance properties from photographs under unknown, real-world illumination conditions. Real-world illumination is complex, with light typically incident on a surface from every direction. We find, however, that real-world illumination patterns are not arbitrary. They exhibit highly predictable spatial structure, which we describe largely in the wavelet domain. Although they differ in several respects from the typical photographs, illumination patterns share much of the regularity described in the natural image statistics literature. These properties of real-world illumination lead to predictable image statistics for a surface with given reflectance properties. We construct a system that classifies a surface according to its reflectance from a single photograph under unknown illuminination. Our algorithm learns relationships between surface reflectance and certain statistics computed from the observed image. Like the human visual system, we solve the otherwise underconstrained inverse problem of reflectance estimation by taking advantage of the statistical regularity of illumination. For surfaces with homogeneous reflectance properties and known geometry, our system rivals human performance.
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The ecotoxicology of nano-TiO2 has been extensively studied in recent years; however, few toxicological investigations have considered the photocatalytic properties of the substance, which can increase its toxicity to aquatic biota. The aim of this work was to evaluate the effects on fish exposed to different nano-TiO2 concentrations and illumination conditions. The interaction of these variables was investigated by observing the survival of the organisms, together with biomarkers of biochemical and genetic alterations. Fish (Piaractus mesopotamicus) were exposed for 96h to 0, 1, 10, and 100mg/L of nano-TiO2, under visible light, and visible light with ultraviolet (UV) light (22.47J/cm2/h). The following biomarkers of oxidative stress were monitored in the liver: concentrations of lipid hydroperoxide and carbonylated protein, and specific activities of superoxide dismutase, catalase, and glutathione S-transferase. Other biomarkers of physiological function were also studied: the specific activities of acid phosphatase and Na,K-ATPase were analyzed in the liver and brain, respectively, and the concentration of metallothionein was measured in the gills. In addition, micronucleus and comet assays were performed with blood as genotoxic biomarkers. Nano-TiO2 caused no mortality under any of the conditions tested, but induced sublethal effects that were influenced by illumination condition. Under both illumination conditions tested, exposure to 100mg/L showed an inhibition of acid phosphatase activity. Under visible light, there was an increase in metallothionein level in fish exposed to 1mg/L of nano-TiO2. Under UV light, protein carbonylation was reduced in groups exposed to 1 and 10mg/L, while nucleus alterations in erythrocytes were higher in fish exposed to 10mg/L. As well as improving the understanding of nano-TiO2 toxicity, the findings demonstrated the importance of considering the experimental conditions in nanoecotoxicological tests. This work provides information for the development of protocols to study substances whose toxicity is affected by illumination conditions. © 2013 Elsevier B.V..
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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We present an image-based method for relighting a scene by analytically fitting cosine lobes to the reflectance function at each pixel, based on gradient illumination photographs. Realistic relighting results for many materials are obtained using a single per-pixel cosine lobe obtained from just two color photographs: one under uniform white illumination and the other under colored gradient illumination. For materials with wavelength-dependent scattering, a better fit can be obtained using independent cosine lobes for the red, green, and blue channels, obtained from three achromatic gradient illumination conditions instead of the colored gradient condition. We explore two cosine lobe reflectance functions, both of which allow an analytic fit to the gradient conditions. One is non-zero over half the sphere of lighting directions, which works well for diffuse and specular materials, but fails for materials with broader scattering such as fur. The other is non-zero everywhere, which works well for broadly scattering materials and still produces visually plausible results for diffuse and specular materials. We also perform an approximate diffuse/specular separation of the reflectance, and estimate scene geometry from the recovered photometric normals to produce hard shadows cast by the geometry, while still reconstructing the input photographs exactly.
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To understand how bees, birds, and fish may use colour vision for food selection and mate choice, we reconstructed views of biologically important objects taking into account the receptor spectral sensitivities. Reflectance spectra a of flowers, bird plumage, and fish skin were used to calculate receptor quantum catches. The quantum catches were then coded by red, green, and blue of a computer monitor; and powers, birds, and fish were visualized in animal colours. Calculations were performed for different illumination conditions. To simulate colour constancy, we used a von Kries algorithm, i.e., the receptor quantum catches were scaled so that the colour of illumination remained invariant. We show that on land this algorithm compensates reasonably well for changes of object appearance caused by natural changes of illumination, while in water failures of von Kries colour constancy are prominent. (C) 2000 John Wiley & Sons, Inc.
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The spectral response and the photocurrent delivered by entirely microcrystalline p-i-n-Si:H detectors an analysed under different applied bias and light illumination conditions. The spectral response and the internal collection depend not only on the energy range but also on the illumination side. Under [p]- and [n]-side irradiation, the internal collection characteristics have an atypical shape. It is high for applied bias and lower than the open circuit voltage, shows a steep decrease near the open circuit voltage (higher under [n]-side illumination) and levels off for higher voltages. Additionally, the numerical modeling of the VIS/NIR detector, based on the band discontinuities near the grain boundaries and interfaces, complements the study and gives insight into the internal physical process.
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A series of large area single layers and heterojunction cells in the assembly glass/ZnO:Al/p (SixC1-x:H)/i (Si:H)/n (SixC1-x:H)/Al (0
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A series of large area single layers and glass/ZnO:AVp(SixC1-x:H)/i(Si:H)/n(SixC1-x:H)/AI (0 < x < 1) heterojunction cells were produced by plasma-enhanced chemical vapour deposition (PE-CVD) at low temperature. Junction properties, carrier transport and photogeneration are investigated from dark and illuminated current-voltage (J-V) and capacitance-voltage (C-V) characteristics. For the heterojunction cells atypical J-V characteristics under different illumination conditions are observed leading to poor fill factors. High series resistances around 106 Q are also measured. These experimental results were used as a basis for the numerical simulation of the energy band diagram, and the electrical field distribution of the structures. Further comparison with the sensor performance gave satisfactory agreement. Results show that the conduction band offset is the most limiting parameter for the optimal collection of the photogenerated carriers. As the optical gap increases and the conductivity of the doped layers decreases, the transport mechanism changes from a drift to a diffusion-limited process.
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In recent works large area hydrogenated amorphous silicon p-i-n structures with low conductivity doped layers were proposed as single element image sensors. The working principle of this type of sensor is based on the modulation, by the local illumination conditions, of the photocurrent generated by a light beam scanning the active area of the device. In order to evaluate the sensor capabilities is necessary to perform a response time characterization. This work focuses on the transient response of such sensor and on the influence of the carbon contents of the doped layers. In order to evaluate the response time a set of devices with different percentage of carbon incorporation in the doped layers is analyzed by measuring the scanner-induced photocurrent under different bias conditions.
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This work presents preliminary results in the study of a novel structure for a laser scanned photodiode (LSP) type of image sensor. In order to increase the signal output, a stacked p-i-n-p-i-n structure with an intermediate light-blocking layer is used. The image and the scanning beam are incident through opposite sides of the sensor and their absorption is kept in separate junctions by an intermediate light-blocking layer. As in the usual LSP structure the scanning beam-induced photocurrent is dependent on the local illumination conditions of the image. The main difference between the two structures arises from the fact that in this new structure the image and the scanner have different optical paths leading to an increase in the photocurrent when the scanning beam is incident on a region illuminated on the image side of the sensor, while a decreasing in the photocurrent was observed in the single junction LSP. The results show that the structure can be successfully used as an image sensor even though some optimization is needed to enhance the performance of the device.
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In this paper a new method for self-localization of mobile robots, based on a PCA positioning sensor to operate in unstructured environments, is proposed and experimentally validated. The proposed PCA extension is able to perform the eigenvectors computation from a set of signals corrupted by missing data. The sensor package considered in this work contains a 2D depth sensor pointed upwards to the ceiling, providing depth images with missing data. The positioning sensor obtained is then integrated in a Linear Parameter Varying mobile robot model to obtain a self-localization system, based on linear Kalman filters, with globally stable position error estimates. A study consisting in adding synthetic random corrupted data to the captured depth images revealed that this extended PCA technique is able to reconstruct the signals, with improved accuracy. The self-localization system obtained is assessed in unstructured environments and the methodologies are validated even in the case of varying illumination conditions.