209 resultados para Image processing -- Digital techniques -- Mathematical models
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The major contribution of this paper relates to the practical advantages of combining Ground Control Points (GCPs), Ground Control Lines (GCLs) and orbital data to estimate the exterior orientation parameters of images collected by CBERS-2B (China-Brazil Earth Resources Satellite) HRC (High-resolution Camera) and CCD (High-resolution CCD Camera) sensors. Although the CBERS-2B is no longer operational, its images are still being used in Brazil, and the next generations of the CBERS satellite will have sensors with similar technical features, which motivates the study presented in this paper. The mathematical models that relate the object and image spaces are based on collinearity (for points) and coplanarity (for lines) conditions. These models were created in an in-house developed software package called TMS (Triangulation with Multiple Sensors) with multi-feature control (GCPs and GCLs). Experiments on a block of four CBERS-2B HRC images and on one CBERS-2B CCD image were performed using both models. It was observed that the combination of GCPs and GCLs provided better bundle block adjustment results than conventional bundle adjustment using only GCPs. The results also demonstrate the advantages of using primarily orbital data when the number of control entities is reduced. © 2013 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS).
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The by-products generated from industrial filleting of tilapia surimi can be used for the manufacture of surimi. The surimi production uses large amounts of water, which generates a wastewater rich in organic compounds (lipids, soluble proteins and blood). Optimizing the number of washing cycles will contribute to a more sustainable production. A mathematical model of mechanically recovered tilapia meat (Oreochromis niloticus) for the processing of surimi (minced fish washing cycles and tapioca starch addition) based on two quality parameters (texture and moisture) was constructed by applying the response surface methodology (RSM). Each factor had an important effect on the moisture and texture of surimi. This study found that the optimal formulation for producing the best surimi using the by-products of tilapia filleting in manufacturing fish burger were the addition of 10% tapioca starch and three minced fish washing cycles. A microstructural evaluation supported the findings of the mathematical model. Practical Applications: The use of mechanically recovered fish meat (MRFM) for the production of surimi enables the utilization of the by-products of filleting fish. However, the inferior quality of the surimi produced from MRFM in relation to that produced with fillets necessitates the addition of starch; secondly, surimi production consumes a large volume of water. RSM provides a valuable means for optimizing the number of washing cycles and starch amounts utilized in fish burger production. Tapioca starch, widely produced in Brazil, has desirable characteristics (surface sheen, smooth texture, neutral taste and clarity in solution) for use in MRFM-produced surimi. © 2013 Wiley Periodicals, Inc.
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Surface defects are extremely important in mechanical characterization of several different materials. Therefore, the analysis of surface finishing is essential for a further simulation of surface mechanical properties in a customized project in materials science and technology. One of the methods commonly employed for such purpose is the statistical mapping of different sample surface regions using the depth from focus technique. The analysis is usually performed directly from the elevation maps which are obtained from the digital image processing. In this paper, the possibility of quantifying the surface heterogeneity of Silicon Carbide porous ceramics by elevation map histograms is presented. The advantage of this technique is that it allows the qualitative or quantitative verification of all surface image fields that cannot be done by using the Surface Plot plugin of image J™ platform commonly used in digital image processing. © 2012 Springer Science+Business Media, LLC.
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Pós-graduação em Ciências Cartográficas - FCT
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Pós-graduação em Biologia Geral e Aplicada - IBB
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Pós-graduação em Ciências Cartográficas - FCT
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Pós-graduação em Ciências Odontológicas - FOAR
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)