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We propose a novel significance measure for skeleton pruning, called bending potential ratio (BPR), in which the decision regarding whether a skeletal branch should be pruned or not is based on the context of the boundary segment ...
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We propose a novel significance measure for skeleton pruning, called bending potential ratio (BPR), in which the decision regarding whether a skeletal branch should be pruned or not is based on the context of the boundary segment that corresponds to the branch. By considering this contextual information, we can better evaluate the contribution of the boundary segment to the overall shape, which generally depends on its particular location within the whole contour (i.e., a segment may be considered to be insignificant in one place while it may be considered as a feature elsewhere). The BPR is a measure of the significance of contour segments in such context, and depicts the bending potential of a contour segment. Unlike other significance measures that only contain local shape information, the BPR evaluates both local and global shape information. Thus, it is insensitive to local boundary deformation. In addition, we also present a scheme for skeleton growing, which integrates pruning based on the BPR measurement. Our experiments demonstrate that the skeletons obtained by the proposed algorithm are medially placed and connected. We also demonstrate that shapes reconstructed from these skeletons are very close to the original shapes. Moreover, the BPR measure yields a natural multi-scale skeletal representation.
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This paper describes an algorithm for au- tomatically generating a control skeleton (sometimes called an IK skeleton) for use in animating a polygonal data model. The algorithm consists of several steps, each of which is performe...
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This paper describes an algorithm for au- tomatically generating a control skeleton (sometimes called an IK skeleton) for use in animating a polygonal data model. The algorithm consists of several steps, each of which is performed automatically. The basic process involves discretizing the figure, com- putting its discrete medial surface (DMS), and then suing the DMS both to create the skeletal structure and to attach the vertices of the model to that structure.
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The problem of generating vector representation of a raster image has been the question of present interest for decades. Although, there are many approaches to this problem, most of them suffer from sophisticated computations and ...
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The problem of generating vector representation of a raster image has been the question of present interest for decades. Although, there are many approaches to this problem, most of them suffer from sophisticated computations and irrational memory usage. We introduce here a new skeletonization agorithm that is very efficient in terms of time and memory consumption. Starting from the description of our approach to the concept of skeleton on raster grid, we present a comprehensive explanation of the algorithm. Its main idea consists of generating a special polyline for each raster line considering them in top-to-bottom direction; skeleton is constructed from points of these polylines. The skeletons obtained by our algorithm allow the precise reconstruction of the initial raster shapes; therefore they may reflect some artifacts possible on raster grid. For this reason, we also present here two algorithms of simplification and our approach to defects filtering on a stage of skeleton generation. The time of simplification by presented algorithms depends linearly on the number of input points that makes these methods fast and efficient. The paper concludes with performance evaluation and discussion of possible implementations of the introduced techniques.
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In this paper we propose a new algorithm for the skeletonization of handwritten characters. Unlike traditional skeletonization algorithms that relay only on the configuration of a binary image pixel in deciding whether it is delet...
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In this paper we propose a new algorithm for the skeletonization of handwritten characters. Unlike traditional skeletonization algorithms that relay only on the configuration of a binary image pixel in deciding whether it is deletable or not, Natural Skeletonization (NS) integrates the gray-level information in this process. The underlying principle here, which stems from the elongated properties of the handwritten characters, is that medial pixels of a handwritten stroke are "naturally" darker than its side pixels. NS consists of three steps: (1) the decomposition step; (2) the thinning step; (3) the reconstruction step. The integration of gray-level information is facilitated by the iterative binarization at equally spaced thresholds, which highlights positional differences between the medial and side pixels of a stroke. The advantage of our approach over existing methods is demonstrated by its ability to prevent the "flooding water" and to prevent the boundary noise from developing extraneous branches. One important aspect of the approach is that it relaxes the skeletonization's dependence on the quality and shape of initial binary pattern. The experimental results indicate that the proposed algorithm substantially improves the skeletonization quality compared to experiments with traditional skeletonization methods.
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Skeleton has been successfully incorporated in the design of high-performance protocol in sensor networks. As there exists a tradeoff between skeleton simplicity and reconstruction error, it is important to quantitatively judge th...
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Skeleton has been successfully incorporated in the design of high-performance protocol in sensor networks. As there exists a tradeoff between skeleton simplicity and reconstruction error, it is important to quantitatively judge the skeleton and refine it properly. While some studies on skeleton extraction and refinement have been proposed, there still lacks deep understanding of quantitative evaluation and skeleton pruning. In this paper, we consider both the simplicity and reconstruction ability of skeleton, and present ESP, an evaluation-based skeleton pruning algorithm. By analyzing the skeleton properties, we first present the adjusted coverage index of skeleton to measure its goodness, and then provide a novel approach for skeleton pruning. We also analyze that the adjusted coverage index is closely related to the performance of skeleton-based applications, and show by simulations that the ESP can correctly judge the skeleton’s goodness and yield a refined skeleton.
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The skeleton driven skinning technique is still the most popular method for animating deformable human and creature characters. Albeit an industry de facto due to its computational performance and intuitiveness, it suffers from pr...
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The skeleton driven skinning technique is still the most popular method for animating deformable human and creature characters. Albeit an industry de facto due to its computational performance and intuitiveness, it suffers from problems like collapsing elbow and candy wrapper joint. To remedy these problems, one needs to formulate the non-linear relationship between the skeleton and the skin shape of a character properly, which however proves mathematically very challenging. Placing additional joints where the skin bends increases the sampling rate and is an ad hoc way of approximating this non-linear relationship. In this paper, we propose a method that is able to accommodate the inherent non-linear relationships between the movement of the skeleton and the skin shape. We use the so-called curve skeletons along with the joint-based skeletons to animate the skin shape. Since the deformation follows the tangent of the curve skeleton and also due to higher sampling rates received from the curve points, collapsing skin and other undesirable skin deformation problems are avoided. The curve skeleton retains the advantages of the current skeleton driven skinning. It is easy to use and allows full control over the animation process. As a further enhancement, it is also fairly simple to build realistic muscle and fat bulge effect. A practical implementation in the form of a Maya plug-in is created to demonstrate the viability of the technique.
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Skeleton is an important topological of an image and is widely used in the fields of image analysis. In this paper, we present an algorithm based on morphological operations for extracting skeleton from a binary image. Since the o...
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Skeleton is an important topological of an image and is widely used in the fields of image analysis. In this paper, we present an algorithm based on morphological operations for extracting skeleton from a binary image. Since the original image can be partially or completely reconstructed from the skeleton, this algorithm which works in both analogue and digital space is useful in image coding and feature description. A fast algorithm for skeletonizing and reconstructing digital images and the results of the fast algorithm are also give.
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We provide simple characterizations of spaces admitting full r-skeletons, c-skeletons and q-skeletons, by using omega-monotone functions. We use this characterization to prove that every countably compact space admitting a full r-...
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We provide simple characterizations of spaces admitting full r-skeletons, c-skeletons and q-skeletons, by using omega-monotone functions. We use this characterization to prove that every countably compact space admitting a full r-skeleton is proximal; furthermore the characterizations are used to show that the class of spaces admitting full c-skeletons is invariant under subspaces, disjoint topological sums and Sigma products, in addition to prove that the class of spaces admitting full q-skeletons is closed under extensions, continuous images and one-point Lindelof extensions of disjoint topological sums. These characterizations also yield some positive results for products. (c) 2021 Elsevier B.V. All rights reserved.
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