The 3D Reconstruction problem from a single endoscope image of a smooth object is studied in the context of the Shape from Shading methods and considering a single light source at the camera projection center. Based o...
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This work reports and illustrates the application of enhancement techniques to images of nervous system from a confocal microscope. These images are processed to enhance regions of interest, e.g. nucleus and nervous t...
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This paper presents a system that is being developed for the recognition of the handwritten legal amount in brazilian bank checks. Our strategy used to approach the handwritten legal amount recognition problem puts on...
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This work aims the recognition of characters in plates of private brazilian vehicles using neural networks. Initially we define a standard for the image as prerequisite for the pre-processing. Afterward, the reduction...
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We present current development towards a real-time method for segmentation of images for robotics applications. Our algorithm follows a fast scan line procedure (rows and columns), thus breaking the 2D segmentation pr...
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This paper proposes an approach for color segmentation which is an alternative to the search of a total order in the color space. Instead of looking for a total order, we look for a suitable metric that defines a colo...
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This work presents a new method for image compression, using Tritree decomposition (TT). TT have been originally proposed by Wille for generation of non-structured finite elements meshs, for numerical solution of diff...
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This paper presents a framework for distributed reactive characters on a computer network and proposes innovative concepts for shared state management. Firstly, behavioral accuracy is defined in terms of three types o...
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This paper presents a technique for the segmentation of moving objects in color image sequences. The technique is based on Beucher-Meyer paradigm, with markers detected by a morphological operator designed by computat...
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We present a technique for accelerating the rendering of high depth-complexity scenes. In a preprocessing stage, we approximate the input model with a hierarchical data structure and compute simple view-dependent poly...
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We present a technique for accelerating the rendering of high depth-complexity scenes. In a preprocessing stage, we approximate the input model with a hierarchical data structure and compute simple view-dependent polygonal occluders to replace the complex input geometry in subsequent visibility queries. When the user is inspecting and visualizing the input model, the computed occluders are used to avoid rendering geometry which cannot be seen. Our method has several advantages which allow it to perform conservative visibility queries efficiently and it does not require any special graphics hardware. The preprocessing step of our approach can also be used within the framework of other visibility culling methods which need to pre-select or pre-render occluders. In this paper, we describe our technique and its implementation in detail, and provide experimental evidence of its performance. In addition, we briefly discuss possible extensions of our algorithm.
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