3 resultados para Orientation Relationship

em Repositório Institucional UNESP - Universidade Estadual Paulista "Julio de Mesquita Filho"


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The identification, characterization and stability range of the phases present in a series of Cu-Al alloys, with Al content from 11.0 to 15.0 wt.%, were studied by Differential Thermal Analysis (DTA), Optical Microscopy (OM), Scanning Electron Microscopy (SEM), Transmission Electron Microscopy (TEM), Selected Area Electron Diffraction (SAED), Auger Electron Spectroscopy (AES), Energy Dispersive X-Ray Spectroscopy (EDX) and X-Ray Diffraction (XRD). In some alloys and in a temperature range from 790 degrees C to 850 degrees C the presence of black spots exhibiting regular shapes and an homogeneous distribution was noticed through metallographic microscopy. Data from TEM and AES indicate that these spots are made of two monocrystalline phases having different Al contents and a crystallographic orientation relationship. (C) 1998 Elsevier B.V. S.A. All rights reserved.

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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This paper presents a method for indirect orientation of aerial images using ground control lines extracted from airborne Laser system (ALS) data. This data integration strategy has shown good potential in the automation of photogrammetric tasks, including the indirect orientation of images. The most important characteristic of the proposed approach is that the exterior orientation parameters (EOP) of a single or multiple images can be automatically computed with a space resection procedure from data derived from different sensors. The suggested method works as follows. Firstly, the straight lines are automatically extracted in the digital aerial image (s) and in the intensity image derived from an ALS data-set (S). Then, correspondence between s and S is automatically determined. A line-based coplanarity model that establishes the relationship between straight lines in the object and in the image space is used to estimate the EOP with the iterated extended Kalman filtering (IEKF). Implementation and testing of the method have employed data from different sensors. Experiments were conducted to assess the proposed method and the results obtained showed that the estimation of the EOP is function of ALS positional accuracy.