950 resultados para Image processing -- Digital techniques


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Image compress consists in represent by small amount of data, without loss a visual quality. Data compression is important when large images are used, for example satellite image. Full color digital images typically use 24 bits to specify the color of each pixel of the Images with 8 bits for each of the primary components, red, green and blue (RGB). Compress an image with three or more bands (multispectral) is fundamental to reduce the transmission time, process time and record time. Because many applications need images, that compression image data is important: medical image, satellite image, sensor etc. In this work a new compression color images method is proposed. This method is based in measure of information of each band. This technique is called by Self-Adaptive Compression (S.A.C.) and each band of image is compressed with a different threshold, for preserve information with better result. SAC do a large compression in large redundancy bands, that is, lower information and soft compression to bands with bigger amount of information. Two image transforms are used in this technique: Discrete Cosine Transform (DCT) and Principal Component Analysis (PCA). Primary step is convert data to new bands without relationship, with PCA. Later Apply DCT in each band. Data Loss is doing when a threshold discarding any coefficients. This threshold is calculated with two elements: PCA result and a parameter user. Parameters user define a compression tax. The system produce three different thresholds, one to each band of image, that is proportional of amount information. For image reconstruction is realized DCT and PCA inverse. SAC was compared with JPEG (Joint Photographic Experts Group) standard and YIQ compression and better results are obtain, in MSE (Mean Square Root). Tests shown that SAC has better quality in hard compressions. With two advantages: (a) like is adaptive is sensible to image type, that is, presents good results to divers images kinds (synthetic, landscapes, people etc., and, (b) it need only one parameters user, that is, just letter human intervention is required

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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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A challenge that remains in the robotics field is how to make a robot to react in real time to visual stimulus. Traditional computer vision algorithms used to overcome this problem are still very expensive taking too long when using common computer processors. Very simple algorithms like image filtering or even mathematical morphology operations may take too long. Researchers have implemented image processing algorithms in high parallelism hardware devices in order to cut down the time spent in the algorithms processing, with good results. By using hardware implemented image processing techniques and a platform oriented system that uses the Nios II Processor we propose an approach that uses the hardware processing and event based programming to simplify the vision based systems while at the same time accelerating some parts of the used algorithms

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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 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.

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OBJETIVO: Quantificar, usando o sistema de imagem digital, medidas palpebrais antes e após a cirurgia de blefaroplastia superior. MÉTODOS: Foram avaliadas 18 pálpebras de 9 pacientes atendidas no HC da FMB - UNESP, com idade entre 40 a 75 anos, do sexo feminino, portadoras de dermatocálase. Foram obtidas fotografias das pacientes antes e após 60 dias da blefaroplastia da pálpebra superior. As imagens foram transferidas para um computador e analisadas pelo programa Scion Image Frame Grabber. Os parâmetros avaliados foram: a altura da fenda palpebral em posição primária do olhar, altura do sulco palpebral superior e o ângulo palpebral lateral antes e depois de 60 dias da realização da cirurgia de blefaroplastia superior. RESULTADOS: Após a cirurgia, houve aumento da altura da fenda palpebral e do sulco palpebral superior. Contudo, o ângulo palpebral lateral não se alterou. CONCLUSÃO: A posição palpebral se altera após a blefaroplastia e o processamento de imagens digitais possibilita quantificar estas alterações, mensurando os resultados obtidos com a cirurgia.

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Mobile robots need autonomy to fulfill their tasks. Such autonomy is related whith their capacity to explorer and to recognize their navigation environments. In this context, the present work considers techniques for the classification and extraction of features from images, using artificial neural networks. This images are used in the mapping and localization system of LACE (Automation and Evolutive Computing Laboratory) mobile robot. In this direction, the robot uses a sensorial system composed by ultrasound sensors and a catadioptric vision system equipped with a camera and a conical mirror. The mapping system is composed of three modules; two of them will be presented in this paper: the classifier and the characterizer modules. Results of these modules simulations are presented in this paper.

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Image orientation is a basic problem in Digital Photogrammetry. While interior and relative orientations were succesfully automated, the same can not be said about absolute orientation. This process can be automated by using an approach based on relational matching and a heuristic that uses the analytical relation between straight features in the object space and its homologous in the image space. A build-in self-diagnosis is also used in this method, that is based on the implementation of data snooping statistic test in the process of spatial resection, using the Iterated Extended Kalman Filtering (IEKF). The aim of this paper is to present the basic principles of the proposed approach and results based on real data.

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Geometric accuracy of a close-range photogrammetric system is assessed in this paper considering surface reconstruction with structured light as its main purpose. The system is based on an off-the-shelf digital camera and a pattern projector. The mathematical model for reconstruction is based on the parametric equation of the projected straight line combined with collinearity equations. A sequential approach for system calibration was developed and is presented. Results obtained from real data are also presented and discussed. Experiments with real data using a prototype have indicated 0.5mm of accuracy in height determination and 0.2mm in the XY plane considering an application where the object was 1630mm distant from the camera.