916 resultados para pipeline image processing
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This article describes the development of a method for analysis of the shape of the stretch zone surface based on parallax measurement theory and using digital image processing techniques. Accurate criteria for the definition of the boundaries of the stretch zone are established from profiles of fracture surfaces obtained from crack tip opening displacement tests on Al-7050 alloy samples. The elevation profiles behavior analysis is based on stretch zone width and height parameters. It is concluded that the geometry of the stretch zone profiles under plane strain conditions can be described by a semi-parabolic relationship. (C) Elsevier B.V., 1999. 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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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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Clustering data is a very important task in data mining, image processing and pattern recognition problems. One of the most popular clustering algorithms is the Fuzzy C-Means (FCM). This thesis proposes to implement a new way of calculating the cluster centers in the procedure of FCM algorithm which are called ckMeans, and in some variants of FCM, in particular, here we apply it for those variants that use other distances. The goal of this change is to reduce the number of iterations and processing time of these algorithms without affecting the quality of the partition, or even to improve the number of correct classifications in some cases. Also, we developed an algorithm based on ckMeans to manipulate interval data considering interval membership degrees. This algorithm allows the representation of data without converting interval data into punctual ones, as it happens to other extensions of FCM that deal with interval data. In order to validate the proposed methodologies it was made a comparison between a clustering for ckMeans, K-Means and FCM algorithms (since the algorithm proposed in this paper to calculate the centers is similar to the K-Means) considering three different distances. We used several known databases. In this case, the results of Interval ckMeans were compared with the results of other clustering algorithms when applied to an interval database with minimum and maximum temperature of the month for a given year, referring to 37 cities distributed across continents
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A 3D binary image is considered well-composed if, and only if, the union of the faces shared by the foreground and background voxels of the image is a surface in R3. Wellcomposed images have some desirable topological properties, which allow us to simplify and optimize algorithms that are widely used in computer graphics, computer vision and image processing. These advantages have fostered the development of algorithms to repair bi-dimensional (2D) and three-dimensional (3D) images that are not well-composed. These algorithms are known as repairing algorithms. In this dissertation, we propose two repairing algorithms, one randomized and one deterministic. Both algorithms are capable of making topological repairs in 3D binary images, producing well-composed images similar to the original images. The key idea behind both algorithms is to iteratively change the assigned color of some points in the input image from 0 (background)to 1 (foreground) until the image becomes well-composed. The points whose colors are changed by the algorithms are chosen according to their values in the fuzzy connectivity map resulting from the image segmentation process. The use of the fuzzy connectivity map ensures that a subset of points chosen by the algorithm at any given iteration is the one with the least affinity with the background among all possible choices
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Data clustering is applied to various fields such as data mining, image processing and pattern recognition technique. Clustering algorithms splits a data set into clusters such that elements within the same cluster have a high degree of similarity, while elements belonging to different clusters have a high degree of dissimilarity. The Fuzzy C-Means Algorithm (FCM) is a fuzzy clustering algorithm most used and discussed in the literature. The performance of the FCM is strongly affected by the selection of the initial centers of the clusters. Therefore, the choice of a good set of initial cluster centers is very important for the performance of the algorithm. However, in FCM, the choice of initial centers is made randomly, making it difficult to find a good set. This paper proposes three new methods to obtain initial cluster centers, deterministically, the FCM algorithm, and can also be used in variants of the FCM. In this work these initialization methods were applied in variant ckMeans.With the proposed methods, we intend to obtain a set of initial centers which are close to the real cluster centers. With these new approaches startup if you want to reduce the number of iterations to converge these algorithms and processing time without affecting the quality of the cluster or even improve the quality in some cases. Accordingly, cluster validation indices were used to measure the quality of the clusters obtained by the modified FCM and ckMeans algorithms with the proposed initialization methods when applied to various data sets
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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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The studied region, named Forquilha and localized in northwestern Central Ceará domain (northern portion of Borborema Province), presents a lithostratigraphic framework constituted by paleoproterozoic metaplutonics, metasedimentary sequences and neoproterozoic granitoids. The metasedimentary rocks of Ceará group occupy most part of the area. This group is subdivided in two distinct units: Canindé and Independência. Canindé unit is represented basically by biotite paragneisses and muscovite paragneisses, with minor metabasic rocks (amphibolite lens). Independência sequence is composed by garnetiferous paragneisses, sillimanite-garnet-quartz-muscovite schists and quartz-muscovite schists, pure or muscovite quartzites and rare marbles. At least three ductile deformation events were recognized in both units of Ceará group, named D1, D2 and D3. The former one is interpreted as related to a low angle tangential tectonics which mass transport is southward. D2 event is marked by the development of close/isoclinal folds with a N-S oriented axis. Refolding patterns generated by F1 and F2 superposition are found in several places. The latest event (D3) corresponds to a transcurrent tectonics, which led to development of mega-folds and several shear zones, under a transpressional regime. The mapped shear zones are Humberto Monte (ZCHM), Poço Cercado (ZCPC) and Forquilha (ZCF). Digital image processing of enhanced Landsat 7-ETM+ satellite images, combined with field data, demonstrate that these penetrative structures are associated with positive and negative geomorphologic patterns, distributed in linear and curvilinear arrangements with tonal banding, corresponding to the ductile fabric and to crests. Diverse color composites were tested and RGB-531 and RGB-752 provided the best results for lineament analysis of the most prominent shear zones. Spatial filtering techniques (3x3 and 5x5 filters) were also used and the application of Prewitt filters generated the best products. The integrated analysis of morphological and textural aspects from filtered images, variation of tonalities related to the distribution of geologic units in color composites and the superposition over a digital elevation model, contributed to a characterization of the structural framework of the study area. Kinematic compatibility of ZCHM, ZCPC, ZCF shear zones, as well as Sobral-Pedro II (ZCSPII) shear zone, situated to the west of the study area, was one of the goal of this work. Two of these shear zones (ZCHM, ZCPC) display sinistral movements, while the others (ZCSPII, ZCF) exhibit dextral kinematics. 40Ar/39Ar ages obtained in this thesis for ZCSPII and ZCPC, associated with other 40Ar/39Ar data of adjacent areas, indicate that all these shear zones are related to Brasiliano orogeny. The trend of the structures, the opposite shear senses and the similar metamorphic conditions are fitted in a model based on the development of conjugate shear zones in an unconfined transpression area. A WNW-ESE bulk shortening direction is infered. The geometry and kinematic of the studied structures suggest that shortening was largely accommodated by lateral extrusion, with only minor amounts of vertical stretch
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The fundamental senses of the human body are: vision, hearing, touch, taste and smell. These senses are the functions that provide our relationship with the environment. The vision serves as a sensory receptor responsible for obtaining information from the outside world that will be sent to the brain. The gaze reflects its attention, intention and interest. Therefore, the estimation of gaze direction, using computer tools, provides a promising alternative to improve the capacity of human-computer interaction, mainly with respect to those people who suffer from motor deficiencies. Thus, the objective of this work is to present a non-intrusive system that basically uses a personal computer and a low cost webcam, combined with the use of digital image processing techniques, Wavelets transforms and pattern recognition, such as artificial neural network models, resulting in a complete system that performs since the image acquisition (including face detection and eye tracking) to the estimation of gaze direction. The obtained results show the feasibility of the proposed system, as well as several feature advantages.
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Purpose: To evaluate reproducibility and precision of ocular measurements by digital photograph analysis, in addition to the transformation of the measures according to the individual iris diameter as an oculometric reference. Methods: Twenty-four eyes have been digitally photographed in a standardized way at two distances. Two researchers have analyzed these printed images using a caliper and these digital forms by ImageJ 1.37 (TM). Several external ocular parameters were estimated (mm and as iris diameter) and methods of measurement compared regarding their precision, agreement and correlation. Results: Caliper and digital analysis of oculometric measures provided significant agreement and correlation, nevertheless the precision of digital measures was higher. The estimates of numeric transformation from oculometric measures according to individual iris diameter resulted in great correlation to caliper measures and high agreement when compared to different distances of taking the photographs. Conclusions: Facial digital photographs allowed oculometric precise and reproducible estimates, endorsing clinical research usefulness. Using iris diameter as individual oculometric reference disclosed high reproducibility when facial photographs were taken at different distances.
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OBJETIVO: Avaliar o desempenho da análise de imagem digital na estimativa da área acometida pelas úlceras crônicas dos membros inferiores. MÉTODOS: Estudo prospectivo em que foram mensuradas úlceras empregando o método planimétrico clássico, utilizando desenho dos seus contornos em filme plástico transparente, medida sua área posteriormente por folha milimetrada. Esses valores foram utilizados como padrão para a comparação com a estimativa de área pelas fotografias digitais padronizadas das úlceras e dos desenhos das mesmas em filme plástico. Para criar um referencial de conversão dos pixels em milímetros, foi empregado um adesivo com tamanho conhecido, adjacente à úlcera. RESULTADOS: foram avaliadas 42 lesões em 20 pacientes portadores de úlceras crônicas de membros inferiores. As áreas das úlceras variaram de 0,24 a 101,65cm². Observou-se forte correlação entre as medidas planimétricas e as fotos das úlceras (R²=0,86 p<0,01), porém a correlação das medidas planimétricas com as fotos digitais dos desenhos das úlceras foi ainda maior (R²=0,99 p<0,01). CONCLUSÃO: A fotografia digital padronizada revelou-se método rápido, preciso e não-invasivo capaz de estimar a área afetada por úlceras. A avaliação das medidas fotográficas dos contornos das úlceras deve ser preferida em relação à análise de sua fotografia direta.
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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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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)