InVesalius is an open-source software for reconstruction of computed tomography and magnetic resonance images, which allows the user to make analysis and segmentation of virtual anatomical models. Physical models can ...InVesalius is an open-source software for reconstruction of computed tomography and magnetic resonance images, which allows the user to make analysis and segmentation of virtual anatomical models. Physical models can be printed with the aid of rapid prototyping, giving the medical community a reliable instrument to help planning surgeries. To offer the user more control over the model, this work describes a methodology and tool developed for NURBS parameterization that provides mechanisms for adjusting the shape or even selecting a particular region of interest of the surface. Furthermore, the tool gives the option to export the final results of the process to a STEP file, which allows further edition in any well-known CAD software.展开更多
Image compression techniques aim to reduce redundant information in order to allow data storage and transmission in an efficient way. In this work, we propose and analyze a lossy image compression method based on the ...Image compression techniques aim to reduce redundant information in order to allow data storage and transmission in an efficient way. In this work, we propose and analyze a lossy image compression method based on the singular value decomposition using an optimal choice of eigenvalues and an adaptive mechanism for block partitioning. Experiments are conducted on several images to demonstrate the effectiveness of the proposed compression method in comparison with the direct application of the singular value decomposition.展开更多
Visual analysis of social networks is usually based on graph drawing algorithms and tools. However, social networks are a special kind of graph in the sense that interpretation of displayed relationships is heavily de...Visual analysis of social networks is usually based on graph drawing algorithms and tools. However, social networks are a special kind of graph in the sense that interpretation of displayed relationships is heavily dependent on context. Context, in its turn, is given by attributes associated with graph elements, such as individual nodes, edges, and groups of edges, as well as by the nature of the connections between individuals. In most systems, attributes of individuals and communities are not taken into consideration during graph layout, except to derive weights for force-based placement strategies. This paper proposes a set of novel tools for displaying and exploring social networks based on attribute and connectivity mappings. These properties are employed to layout nodes on the plane via multidimensional projection techniques. For the attribute mapping, we show that node proximity in the layout corresponds to similarity in atgribute, leading to easiness in locating similar groups of nodes. The projection based on connectivity yields an initial placement that forgoes force-based or graph analysis algorithm, reaching a meaningful layout in one pass. When a force algorithm is then applied to this initial mapping, the final layout presents better properties than conventional force-based approaches. Numerical evaluations show a number of advantages of pre-mapping points via projections. User evaluation demonstrates that these tools promote ease of manipulation as well as fast identification of concepts and associations which cannot be easily expressed by conventional graph visualization alone. In order to allow better space usage for complex networks, a graph mapping on the surface of a sphere is also implemented.展开更多
Sugarcane planting is an important and growing activity in Brazil.Thereupon,several techniques have been developed over the years to maximize crop productivity and profit,amongst them,processing of sugarcane field ima...Sugarcane planting is an important and growing activity in Brazil.Thereupon,several techniques have been developed over the years to maximize crop productivity and profit,amongst them,processing of sugarcane field images.In this sense,this research aims to identify and analyze crop rows and measure their gaps from aerial images of sugarcane fields.For this,a small Remotely Piloted Aircraft captured the images,generating orthomosaics of the areas for analysis.Then,each orthomosaic is classified with the K-Nearest Neighbor algorithm to segment regions of interest.Planting row orientation is estimated using the RGB gradient filter.Morphological operations and computational geometry models are then used to detect and map rows and gaps along the planting row segment.To evaluate the results,crop rows are mapped and compared to manually taken measurements.Our technique obtained an error smaller than 2%when compared to gap length in crop rows from an orthomosaic with the area of 8.05 ha(ha).The proposed approach can map the positioning of the automatically generated row segments appropriately onto manually created segments.Moreover,our method also achieved similar results when confronted with a manual technique for differing growth stages(40 and 80 days after harvest)of the sugarcane crop.The proposed method presents a great potential to be adopted in sugarcane planting monitoring。展开更多
文摘InVesalius is an open-source software for reconstruction of computed tomography and magnetic resonance images, which allows the user to make analysis and segmentation of virtual anatomical models. Physical models can be printed with the aid of rapid prototyping, giving the medical community a reliable instrument to help planning surgeries. To offer the user more control over the model, this work describes a methodology and tool developed for NURBS parameterization that provides mechanisms for adjusting the shape or even selecting a particular region of interest of the surface. Furthermore, the tool gives the option to export the final results of the process to a STEP file, which allows further edition in any well-known CAD software.
文摘Image compression techniques aim to reduce redundant information in order to allow data storage and transmission in an efficient way. In this work, we propose and analyze a lossy image compression method based on the singular value decomposition using an optimal choice of eigenvalues and an adaptive mechanism for block partitioning. Experiments are conducted on several images to demonstrate the effectiveness of the proposed compression method in comparison with the direct application of the singular value decomposition.
基金FAPESP, CNPq and CAPES for their financial support
文摘Visual analysis of social networks is usually based on graph drawing algorithms and tools. However, social networks are a special kind of graph in the sense that interpretation of displayed relationships is heavily dependent on context. Context, in its turn, is given by attributes associated with graph elements, such as individual nodes, edges, and groups of edges, as well as by the nature of the connections between individuals. In most systems, attributes of individuals and communities are not taken into consideration during graph layout, except to derive weights for force-based placement strategies. This paper proposes a set of novel tools for displaying and exploring social networks based on attribute and connectivity mappings. These properties are employed to layout nodes on the plane via multidimensional projection techniques. For the attribute mapping, we show that node proximity in the layout corresponds to similarity in atgribute, leading to easiness in locating similar groups of nodes. The projection based on connectivity yields an initial placement that forgoes force-based or graph analysis algorithm, reaching a meaningful layout in one pass. When a force algorithm is then applied to this initial mapping, the final layout presents better properties than conventional force-based approaches. Numerical evaluations show a number of advantages of pre-mapping points via projections. User evaluation demonstrates that these tools promote ease of manipulation as well as fast identification of concepts and associations which cannot be easily expressed by conventional graph visualization alone. In order to allow better space usage for complex networks, a graph mapping on the surface of a sphere is also implemented.
基金Sao Paulo Research Founda-tion(FAPESP grant#2017/12646-3)National Council for Scien-tific and Technological Development(CNPq grant#309330/2018-1)Coordination for the Improvement of Higher Education Personnel(CAPES Finance Code#001)for their financial support.
文摘Sugarcane planting is an important and growing activity in Brazil.Thereupon,several techniques have been developed over the years to maximize crop productivity and profit,amongst them,processing of sugarcane field images.In this sense,this research aims to identify and analyze crop rows and measure their gaps from aerial images of sugarcane fields.For this,a small Remotely Piloted Aircraft captured the images,generating orthomosaics of the areas for analysis.Then,each orthomosaic is classified with the K-Nearest Neighbor algorithm to segment regions of interest.Planting row orientation is estimated using the RGB gradient filter.Morphological operations and computational geometry models are then used to detect and map rows and gaps along the planting row segment.To evaluate the results,crop rows are mapped and compared to manually taken measurements.Our technique obtained an error smaller than 2%when compared to gap length in crop rows from an orthomosaic with the area of 8.05 ha(ha).The proposed approach can map the positioning of the automatically generated row segments appropriately onto manually created segments.Moreover,our method also achieved similar results when confronted with a manual technique for differing growth stages(40 and 80 days after harvest)of the sugarcane crop.The proposed method presents a great potential to be adopted in sugarcane planting monitoring。
