926 resultados para Image processing -- Digital techniques -- Mathematical models
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The vision is one of the five senses of the human body and, in children is responsible for up to 80% of the perception of world around. Studies show that 50% of children with multiple disabilities have some visual impairment, and 4% of all children are diagnosed with strabismus. The strabismus is an eye disability associated with handling capacity of the eye, defined as any deviation from perfect ocular alignment. Besides of aesthetic aspect, the child may report blurred or double vision . Ophthalmological cases not diagnosed correctly are reasons for many school abandonments. The Ministry of Education of Brazil points to the visually impaired as a challenge to the educators of children, particularly in literacy process. The traditional eye examination for diagnosis of strabismus can be accomplished by inducing the eye movements through the doctor s instructions to the patient. This procedure can be played through the computer aided analysis of images captured on video. This paper presents a proposal for distributed system to assist health professionals in remote diagnosis of visual impairment associated with motor abilities of the eye, such as strabismus. It is hoped through this proposal to contribute improving the rates of school learning for children, allowing better diagnosis and, consequently, the student accompaniment
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Environmental sustainability has become one of the topics of greatest interest in industry, mainly due to effluent generation. Phenols are found in many industries effluents, these industries might be refineries, coal processing, pharmaceutical, plastics, paints and paper and pulp industries. Because phenolic compounds are toxic to humans and aquatic organisms, Federal Resolution CONAMA No. 430 of 13.05.2011 limits the maximum content of phenols, in 0.5 mg.L-1, for release in freshwater bodies. In the effluents treatment, the liquid-liquid extraction process is the most economical for the phenol recovery, because consumes little energy, but in most cases implements an organic solvent, and the use of it can cause some environmental problems due to the high toxicity of this compound. Because of this, exists a need for new methodologies, which aims to replace these solvents for biodegradable ones. Some literature studies demonstrate the feasibility of phenolic compounds removing from aqueous effluents, by biodegradable solvents. In this extraction kind called "Cloud Point Extraction" is used a nonionic surfactant as extracting agent of phenolic compounds. In order to optimize the phenol extraction process, this paper studies the mathematical modeling and optimization of extraction parameters and investigates the effect of the independent variables in the process. A 32 full factorial design has been done with operating temperature and surfactant concentration as independent variables and, parameters extraction: Volumetric fraction of coacervate phase, surfactant and residual concentration of phenol in dilute phase after separation phase and phenol extraction efficiency, as dependent variables. To achieve the objectives presented before, the work was carried out in five steps: (i) selection of some literature data, (ii) use of Box-Behnken model to find out mathematical models that describes the process of phenol extraction, (iii) Data analysis were performed using STATISTICA 7.0 and the analysis of variance was used to assess the model significance and prediction (iv) models optimization using the response surface method (v) Mathematical models validation using additional measures, from samples different from the ones used to construct the model. The results showed that the mathematical models found are able to calculate the effect of the surfactant concentration and the operating temperature in each extraction parameter studied, respecting the boundaries used. The models optimization allowed the achievement of consistent and applicable results in a simple and quick way leading to high efficiency in process operation.
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When GNSS receivers capable of collecting dual-frequency data are available, it is possible to eliminate the first-order ionospheric effect in the data processing through the ionosphere-free linear combination. However, the second- and third-order ionospheric effects still remain. The first-, second- and third-order ionospheric effects are directly proportional to the total electron content (TEC), although the second- and third-order effects are influenced, respectively, by the geomagnetic field and the maximum electron density. In recent years, the international scientific community has given more attention to these kinds of effects and some works have shown that for high precision GNSS positioning these effects have to be taken into consideration. We present a software tool called RINEX_HO that was developed to correct GPS observables for second- and third-order ionosphere effects. RINEX_HO requires as input a RINEX observation file, then computes the second- and third-order ionospheric effects, and applies the corrections to the original GPS observables, creating a corrected RINEX file. The mathematical models implemented to compute these effects are presented, as well as the transformations involving the earth's magnetic field. The use of TEC from global ionospheric maps and TEC calculated from raw pseudorange measurements or pseudoranges smoothed by phase is also investigated.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Considering the growing use of digital cameras in Photogrammetric projects, especially in aerial survey, this paper presents tests and analyses of bundle block adjustment with additional parameters, using different mathematical models, and blocks of images acquired by the SAAPI digital acquisition system. Three blocks of images were processed by the LPS (Leica Photogrammetry Suite) software, in which five groups of additional parameters (AP) can be used: Bauer, Jacobsen, Ebner, Brown and Lens distortion. These AP's models were employed in the bundle block adjustment, and the results were analyzed based on the accuracy of the checking points and on the changes in these additional parameters. The obtained results showed that the Lens Distortion model allowed the best results.
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A method has been developed to obtain quantitative information about grain size and shape from fractured surfaces of ceramic materials. One elaborated a routine to split intergranular and transgranular grains facets of ceramic fracture surfaces by digital image processing. A commercial ceramic (ALCOA A-16, Al2O3-1.5% of CrO) was used to test the proposed method. Microstructural measurements of grain shape and size taken from fracture surfaces have been compared through descriptive statistics of distributions, with the corresponding measurements from polished and etched surfaces. The agreement between results, with the expected bias on grain size values from fractures, obtained for both types of surfaces allowed to infer that this new technique can be used to extract the relevant microstructural information from fractured surfaces, thus minimising the time consuming steps of sample preparation. (C) 2003 Elsevier Ltd. All rights reserved.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Digital image processing is a field that demands great processing capacity. As such it becomes relevant to implement software that is based on the distribution of the processing into several nodes divided by computers belonging to the same network. Specifically discussed in this work are distributed algorithms of compression and expansion of images using the discrete cosine transform. The results show that the savings in processing time obtained due to the parallel algorithms in comparison to its sequential equivalents is a function that depends on the resolution of the image and the complexity of the involved calculation; that is efficiency is greater the longer the processing period is in terms of the time involved for the communication between the network points.
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Image segmentation is the process of subdiving an image into constituent regions or objects that have similar features. In video segmentation, more than subdividing the frames in object that have similar features, there is a consistency requirement among segmentations of successive frames of the video. Fuzzy segmentation is a region growing technique that assigns to each element in an image (which may have been corrupted by noise and/or shading) a grade of membership between 0 and 1 to an object. In this work we present an application that uses a fuzzy segmentation algorithm to identify and select particles in micrographs and an extension of the algorithm to perform video segmentation. Here, we treat a video shot is treated as a three-dimensional volume with different z slices being occupied by different frames of the video shot. The volume is interactively segmented based on selected seed elements, that will determine the affinity functions based on their motion and color properties. The color information can be extracted from a specific color space or from three channels of a set of color models that are selected based on the correlation of the information from all channels. The motion information is provided into the form of dense optical flows maps. Finally, segmentation of real and synthetic videos and their application in a non-photorealistic rendering (NPR) toll are presented
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This work has as main objective to find mathematical models based on linear parametric estimation techniques applied to the problem of calculating the grow of gas in oil wells. In particular we focus on achieving grow models applied to the case of wells that produce by plunger-lift technique on oil rigs, in which case, there are high peaks in the grow values that hinder their direct measurement by instruments. For this, we have developed estimators based on recursive least squares and make an analysis of statistical measures such as autocorrelation, cross-correlation, variogram and the cumulative periodogram, which are calculated recursively as data are obtained in real time from the plant in operation; the values obtained for these measures tell us how accurate the used model is and how it can be changed to better fit the measured values. The models have been tested in a pilot plant which emulates the process gas production in oil wells
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Image segmentation is the process of labeling pixels on di erent objects, an important step in many image processing systems. This work proposes a clustering method for the segmentation of color digital images with textural features. This is done by reducing the dimensionality of histograms of color images and using the Skew Divergence to calculate the fuzzy a nity functions. This approach is appropriate for segmenting images that have colorful textural features such as geological, dermoscopic and other natural images, as images containing mountains, grass or forests. Furthermore, experimental results of colored texture clustering using images of aquifers' sedimentary porous rocks are presented and analyzed in terms of precision to verify its e ectiveness.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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The study area is located on the Brazilian Continental Shelf adjacent to Ceará State, inserted in the submerged Potiguar Basin. This area was submitted to extensional efforts during Upper Cretaceous, associated to the begining of the rifting that resulted in African and South American Continent separation. The main goal of this research was to better understand the sedimentary and geomorphological characteristics of the continental shelf adjacent to Fortim, Aracati and Icapuí (Ceará State). The used data base included geophysical (sides scan sonar and bathymetry studies) and sedimentological survey, associated to satellite image processing and interpretation. Inferences about suspended material and longshore drift was possible using satellite images, and differente bedforms were characterized such as: different kinds of dunes (longitudinal, cross and oblique), bioclastic banks, paleochannels, flat and rock bottom. The researched area comprehended about 2509,13 km2, where 6 different sedimentary facies, based on sediment composition and texture, could be recognized, such as: Bioclastic Sand, Siliciclastic Sand, Biosiliciclastic Sand, Bioclastic gravel, Biosiliciclastic sand with granule and gravel, and Silicibioclastic sand with granule and gravel. The integration of bathymetric, satellite image, side scan sonar and sedimentological data allow us a better characterization of this continental shelf area, as to advance in the knowledge of the continental shelf of the state of Ceara, a very important area to the oil industry because of its potential exploration and e exploitation, and to environmental survey as well
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OBJETIVO: Avaliar a posição do supercílio em diferentes idades, utilizando medidas angulares. MÉTODOS: Foram avaliados indivíduos com idade de 4 a 6 anos (Grupo de crianças) e igual ou superior a 50 anos (Grupo de idosos), separados em faixas etárias, avaliando-se a posição do supercílio por meio de imagens digitais, utilizando medidas angulares. As imagens foram tomadas em posição primária do olhar, utilizando filmadora Sony Lithium, e posteriormente transferidas para computador MacIntosh G4 e processadas pelo programa NIH 1,58. Os parâmetros analisados foram: ângulo interno, externo e vertical da cauda do supercílio. As comparações foram entre sexos, faixas etárias e lateralidade. Os resultados obtidos foram submetidos à análise estatística. RESULTADOS: A comparação das medidas angulares mostrou que houve diferença significativa na posição da cauda do supercílio entre os grupos estudados quando comparados dentro do grupo com faixa etária semelhante. Porém, comparando-se crianças e adultos, houve diferença em todos os tipos de ângulos estudados. CONCLUSÕES: A posição do supercílio avaliada por medidas angulares mostrou diferenças entre crianças e idosos, revelando associação positiva com a idade.