20 resultados para Texture segmentation


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A 7.4 mm thick strip of 3003 aluminum alloy produced by the industrial twin-roll casting (TRC) process was homogenized at 500 °C for 12 hours, after which it was cold rolled in two conditions: 1) to reduce the strip's thickness by 67%, and 2) to reduce it by 91%. The alloy was annealed at 400 °C for 1 hour in both conditions. The results revealed that a rotated cube texture, the {001}<110> component, predominated in the as-cast condition and was transformed into brass, copper and S type textures during the cold rolling process. There was practically no difference between the deformation textures at the two thickness reductions.

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The parenchymal distribution of the splenic artery was studied in order to obtain anatomical basis for partial splenectomy. Thirty two spleens were studied, 26 spleens of healthy horses weighing 320 to 450kg, aged 3 to 12 years and 6 spleens of fetus removed from slaughterhouse. The spleens were submitted to arteriography and scintigraphy in order to have their vascular pattern examined and compared to the external aspect of the organ aiming establish anatomo-surgical segments. All radiographs were photographed with a digital camera and the digital images were submitted to a measuring system for comparative analysis of areas of dorsal and ventral anatomo-surgical segments. Anatomical investigations into the angioarchitecture of the equine spleen showed a paucivascular area, which coincides with a thinner external area, allowing the organ to be divided in two anatomo-surgical segments of approximately 50% of the organ each.

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This work proposes a novel texture descriptor based on fractal theory. The method is based on the Bouligand- Minkowski descriptors. We decompose the original image recursively into four equal parts. In each recursion step, we estimate the average and the deviation of the Bouligand-Minkowski descriptors computed over each part. Thus, we extract entropy features from both average and deviation. The proposed descriptors are provided by concatenating such measures. The method is tested in a classification experiment under well known datasets, that is, Brodatz and Vistex. The results demonstrate that the novel technique achieves better results than classical and state-of-the-art texture descriptors, such as Local Binary Patterns, Gabor-wavelets and co-occurrence matrix.

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In this paper,we present a novel texture analysis method based on deterministic partially self-avoiding walks and fractal dimension theory. After finding the attractors of the image (set of pixels) using deterministic partially self-avoiding walks, they are dilated in direction to the whole image by adding pixels according to their relevance. The relevance of each pixel is calculated as the shortest path between the pixel and the pixels that belongs to the attractors. The proposed texture analysis method is demonstrated to outperform popular and state-of-the-art methods (e.g. Fourier descriptors, occurrence matrix, Gabor filter and local binary patterns) as well as deterministic tourist walk method and recent fractal methods using well-known texture image datasets.

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The strength and durability of materials produced from aggregates (e.g., concrete bricks, concrete, and ballast) are critically affected by the weathering of the particles, which is closely related to their mineral composition. It is possible to infer the degree of weathering from visual features derived from the surface of the aggregates. By using sound pattern recognition methods, this study shows that the characterization of the visual texture of particles, performed by using texture-related features of gray scale images, allows the effective differentiation between weathered and nonweathered aggregates. The selection of the most discriminative features is also performed by taking into account a feature ranking method. The evaluation of the methodology in the presence of noise suggests that it can be used in stone quarries for automatic detection of weathered materials.