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Статті в журналах з теми "Topological skeletonization"

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Автор: Grafiati

Опубліковано: 25 травня 2022

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Rokicki, Jarek. "SURVEY OF SKELETONIZATION METHODS." Mokslas - Lietuvos ateitis 2, no. 1 (February 28, 2010): 19–22. http://dx.doi.org/10.3846/mla.2010.004.

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In this article we present a brief survey on skeletons. The skeleton types are reviewed and definitions given for each of them. The desirable skeleton properties are named: centred, thin, robust, connected, indexed, smooth, reliable and reconstructable. Also different methods groups of skeleton extraction are discussed based on: topological thinning, distance transform, geometrical, path planning, general field and propagating waves. Advantages and disadvantages are discussed for each of them.

Giuliani, Donatella. "A Robust Skeletonization Method for Topological Complex Shapes." International Journal of Computer Vision and Image Processing 7, no. 1 (January 2017): 1–18. http://dx.doi.org/10.4018/ijcvip.2017010101.

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In this paper, we describe a skeletonization method effective and robust when applied to complex shapes, even if affected by boundary perturbations. This approach has been applied to binary segmented images containing bi-dimensional bounded shapes, generally not simply connected. It has been considered an external force field derived by an anisotropic flow. Through the divergence, we have examined the field flow at different times, discovering that the field divergence satisfies an anisotropic diffusion equation as well. Curves of positive divergence may be thought as propagating fronts converging to a steady state formed by shocks points. It has been proved that the sets of points, inside the shape, where divergence assumes positive values, converge to the skeleton. The curves with negative values of divergence remain static, so they may be directly used for edge extraction. This methodology has also been tested respect to boundary perturbations and disconnections.

HAMAOKA, Aya, Issei FUJISHIRO, Shigeo TAKAHASHI, and Yuriko TAKESHIMA. "Topological Skeletonization of Time-Varying Volumes and its Applications." Journal of the Visualization Society of Japan 23, Supplement1 (2003): 391–94. http://dx.doi.org/10.3154/jvs.23.supplement1_391.

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He, Wenyun, Thomas A. Hamilton, Andrew R. Cohen, Timothy J. Holmes, Christopher Pace, Donald H. Szarowski, James N. Turner, and Badrinath Roysam. "Automated Three-Dimensional Tracing of Neurons in Confocal and Brightfield Images." Microscopy and Microanalysis 9, no. 4 (August 2003): 296–310. http://dx.doi.org/10.1017/s143192760303040x.

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Automated three-dimensional (3-D) image analysis methods are presented for tracing of dye-injected neurons imaged by fluorescence confocal microscopy and HRP-stained neurons imaged by transmitted-light brightfield microscopy. An improved algorithm for adaptive 3-D skeletonization of noisy images enables the tracing. This algorithm operates by performing connectivity testing over large N × N × N voxel neighborhoods exploiting the sparseness of the structures of interest, robust surface detection that improves upon classical vacant neighbor schemes, improved handling of process ends or tips based on shape collapse prevention, and thickness-adaptive thinning. The confocal image stacks were skeletonized directly. The brightfield stacks required 3-D deconvolution. The results of skeletonization were analyzed to extract a graph representation. Topological and metric analyses can be carried out using this representation. A semiautomatic method was developed for reconnection of dendritic fragments that are disconnected due to insufficient dye penetration, an imaging deficiency, or skeletonization errors.

Takahashi, Shigeo, Yuriko Takeshima, and Issei Fujishiro. "Topological volume skeletonization and its application to transfer function design." Graphical Models 66, no. 1 (January 2004): 24–49. http://dx.doi.org/10.1016/j.gmod.2003.08.002.

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Chinara, Chinmay. "A Novel Approach To Topological Skeletonization Of English Alphabets And Characters." IOSR Journal of Computer Engineering 2, no. 5 (2012): 38–42. http://dx.doi.org/10.9790/0661-0253842.

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原, 凤英. "Research on GVF Skeletonization Extraction Algorithm Based on Topological Analysis of Regions Division." Optoelectronics 11, no. 03 (2021): 125–31. http://dx.doi.org/10.12677/oe.2021.113015.

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Liebscher, André, and Claudia Redenbach. "STATISTICAL ANALYSIS OF THE LOCAL STRUT THICKNESS OF OPEN CELL FOAMS." Image Analysis & Stereology 32, no. 1 (March 19, 2013): 1. http://dx.doi.org/10.5566/ias.v32.p1-12.

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Open cell foams are formed by an interconnected network of struts whose thickness varies locally. These variations were shown to have an impact on the elastic and thermal properties of the foam. In this paper we quantify the local strut thickness by means of micro computed tomography (µCT) imaging. We introduce a skeletonization based topological decomposition of the foam structure into its vertices and struts. This allows to estimate the thickness of individual strut segments by the Euclidean distance transform, where an appropriate correction for struts with nonspherical cross-sectional shape is applied. Conflating these estimates based on the strut lengths results in a strut thickness profile for the entire foam. Polynomial models for the strut thickness profile are investigated by means of a regression analysis.

KUDELSKI, DIMITRI, SOPHIE VISEUR, GIOVANNI SCROFANI, and JEAN-LUC MARI. "FEATURE LINE EXTRACTION ON MESHES THROUGH VERTEX MARKING AND 2D TOPOLOGICAL OPERATORS." International Journal of Image and Graphics 11, no. 04 (October 2011): 531–48. http://dx.doi.org/10.1142/s0219467811004226.

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Classical approaches of feature line detection rely on curvature derivatives. They generally suffer from a common problem: the connectivity is hard to obtain and it is impossible to generate intersections between feature lines. This article presents a method to extract feature lines on 3D meshes. In order to sort out the recurrent issues of traditional approaches, we propose a novel algorithm based on two ideas. First, all the mesh vertices are marked according to the curvature values: a binary map with candidate regions is then constructed. The second idea is to isolate each candidate region and transform it into a line. To achieve this, we parameterize the region into its 2D regular representation. We then perform a skeletonization to obtain lines with high connectivity. By applying the inverse parameterization, the feature lines are mapped back onto the 3D mesh. In the end, we extract perceptual salient parts and above all connected feature lines. In order to evaluate and validate our algorithm, we compare our method to classical ones and apply our technique to a geological context.

Liang, Z., M. A. Ioannidis, and I. Chatzis. "Geometric and Topological Analysis of Three-Dimensional Porous Media: Pore Space Partitioning Based on Morphological Skeletonization." Journal of Colloid and Interface Science 221, no. 1 (January 2000): 13–24. http://dx.doi.org/10.1006/jcis.1999.6559.

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Buczek, Michał Mateusz. "Area collapse algorithm computing new curve of 2D geometric objects." Geodesy and Cartography 66, no. 1 (June 1, 2017): 23–43. http://dx.doi.org/10.1515/geocart-2017-0004.

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Abstract The processing of cartographic data demands human involvement. Up-to-date algorithms try to automate a part of this process. The goal is to obtain a digital model, or additional information about shape and topology of input geometric objects. A topological skeleton is one of the most important tools in the branch of science called shape analysis. It represents topological and geometrical characteristics of input data. Its plot depends on using algorithms such as medial axis, skeletonization, erosion, thinning, area collapse and many others. Area collapse, also known as dimension change, replaces input data with lower-dimensional geometric objects like, for example, a polygon with a polygonal chain, a line segment with a point. The goal of this paper is to introduce a new algorithm for the automatic calculation of polygonal chains representing a 2D polygon. The output is entirely contained within the area of the input polygon, and it has a linear plot without branches. The computational process is automatic and repeatable. The requirements of input data are discussed. The author analyzes results based on the method of computing ends of output polygonal chains. Additional methods to improve results are explored. The algorithm was tested on real-world cartographic data received from BDOT/GESUT databases, and on point clouds from laser scanning. An implementation for computing hatching of embankment is described.

Bulatov, D., S. Wenzel, G. Häufel, and J. Meidow. "CHAIN-WISE GENERALIZATION OF ROAD NETWORKS USING MODEL SELECTION." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences IV-1/W1 (May 30, 2017): 59–66. http://dx.doi.org/10.5194/isprs-annals-iv-1-w1-59-2017.

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Streets are essential entities of urban terrain and their automatized extraction from airborne sensor data is cumbersome because of a complex interplay of geometric, topological and semantic aspects. Given a binary image, representing the road class, centerlines of road segments are extracted by means of skeletonization. The focus of this paper lies in a well-reasoned representation of these segments by means of geometric primitives, such as straight line segments as well as circle and ellipse arcs. We propose the fusion of raw segments based on similarity criteria; the output of this process are the so-called chains which better match to the intuitive perception of what a street is. Further, we propose a two-step approach for chain-wise generalization. First, the chain is pre-segmented using <ttt>circlePeucker</ttt> and finally, model selection is used to decide whether two neighboring segments should be fused to a new geometric entity. Thereby, we consider both variance-covariance analysis of residuals and model complexity. The results on a complex data-set with many traffic roundabouts indicate the benefits of the proposed procedure.

Fujimori, Tomoyuki, Hiromasa Suzuki, Yohei Kobayashi, and Kiwamu Kase. "Contouring Medial Surface of Thin-Plate Structures Using Local Marching Cubes." Journal of Computing and Information Science in Engineering 5, no. 2 (February 22, 2005): 111–15. http://dx.doi.org/10.1115/1.1891823.

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This paper describes a new algorithm for contouring a medial surface from CT (computed tomography) data of a thin-plate structure. Thin-plate structures are common in mechanical structures, such as car body shells. When designing thin-plate structures in CAD (computer-aided design) and CAE (computer-aided engineering) systems, their shapes are usually represented as surface models associated with their thickness values. In this research, we are aiming at extracting medial surface models of thin-plate structures from their CT data for use in CAD and CAE systems. Commonly used isosurfacing methods, such as marching cubes, are not applicable to contour the medial surface. Therefore, we first extract medial cells (cubes comprising eight neighboring voxels) from the CT data using a skeletonization method to apply the marching cubes algorithm for extracting the medial surface. It is not, however, guaranteed that the marching cubes algorithm can contour those medial cells (in short, not “marching cubeable”). In this study, therefore we developed cell operations that correct topological connectivity to guarantee such marching cubeability. We then use this method to assign virtual signs to the voxels to apply the marching cubes algorithm to generate triangular meshes of a medial surface and map the thicknesses of thin-plate structures to the triangle meshes as textures. A prototype system was developed to verify some experimental results.

Zhou, Bin, Zhendong Zhang, Ji Wang, Y. Eric Yu, X. Sherry Liu, Kyle K. Nishiyama, Mishaela R. Rubin, Elizabeth Shane, John P. Bilezikian, and X. Edward Guo. "In vivo precision of digital topological skeletonization based individual trabecula segmentation (ITS) analysis of trabecular microstructure at the distal radius and tibia by HR-pQCT." Pattern Recognition Letters 76 (June 2016): 83–89. http://dx.doi.org/10.1016/j.patrec.2015.03.012.

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Tan, Hai, Dadong Wang, Rongxin Li, Changming Sun, Ryan Lagerstrom, You He, Yanling Xue, and Tiqiao Xiao. "A robust method for high-precision quantification of the complex three-dimensional vasculatures acquired by X-ray microtomography." Journal of Synchrotron Radiation 23, no. 5 (August 11, 2016): 1216–26. http://dx.doi.org/10.1107/s1600577516011498.

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The quantification of micro-vasculatures is important for the analysis of angiogenesis on which the detection of tumor growth or hepatic fibrosis depends. Synchrotron-based X-ray computed micro-tomography (SR-µCT) allows rapid acquisition of micro-vasculature images at micrometer-scale spatial resolution. Through skeletonization, the statistical features of the micro-vasculature can be extracted from the skeleton of the micro-vasculatures. Thinning is a widely used algorithm to produce the vascular skeleton in medical research. Existing three-dimensional thinning methods normally emphasize the preservation of topological structure rather than geometrical features in generating the skeleton of a volumetric object. This results in three problems and limits the accuracy of the quantitative results related to the geometrical structure of the vasculature. The problems include the excessively shortened length of elongated objects, eliminated branches of blood vessel tree structure, and numerous noisy spurious branches. The inaccuracy of the skeleton directly introduces errors in the quantitative analysis, especially on the parameters concerning the vascular length and the counts of vessel segments and branching points. In this paper, a robust method using a consolidated end-point constraint for thinning, which generates geometry-preserving skeletons in addition to maintaining the topology of the vasculature, is presented. The improved skeleton can be used to produce more accurate quantitative results. Experimental results from high-resolution SR-µCT images show that the end-point constraint produced by the proposed method can significantly improve the accuracy of the skeleton obtained using the existingITKthree-dimensional thinning filter. The produced skeleton has laid the groundwork for accurate quantification of the angiogenesis. This is critical for the early detection of tumors and assessing anti-angiogenesis treatments.

Zeng, Dan, Mao Li, Ni Jiang, Yiwen Ju, Hannah Schreiber, Erin Chambers, David Letscher, Tao Ju, and Christopher N. Topp. "TopoRoot: a method for computing hierarchy and fine-grained traits of maize roots from 3D imaging." Plant Methods 17, no. 1 (December 2021). http://dx.doi.org/10.1186/s13007-021-00829-z.

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Abstract Background 3D imaging, such as X-ray CT and MRI, has been widely deployed to study plant root structures. Many computational tools exist to extract coarse-grained features from 3D root images, such as total volume, root number and total root length. However, methods that can accurately and efficiently compute fine-grained root traits, such as root number and geometry at each hierarchy level, are still lacking. These traits would allow biologists to gain deeper insights into the root system architecture. Results We present TopoRoot, a high-throughput computational method that computes fine-grained architectural traits from 3D images of maize root crowns or root systems. These traits include the number, length, thickness, angle, tortuosity, and number of children for the roots at each level of the hierarchy. TopoRoot combines state-of-the-art algorithms in computer graphics, such as topological simplification and geometric skeletonization, with customized heuristics for robustly obtaining the branching structure and hierarchical information. TopoRoot is validated on both CT scans of excavated field-grown root crowns and simulated images of root systems, and in both cases, it was shown to improve the accuracy of traits over existing methods. TopoRoot runs within a few minutes on a desktop workstation for images at the resolution range of 400^3, with minimal need for human intervention in the form of setting three intensity thresholds per image. Conclusions TopoRoot improves the state-of-the-art methods in obtaining more accurate and comprehensive fine-grained traits of maize roots from 3D imaging. The automation and efficiency make TopoRoot suitable for batch processing on large numbers of root images. Our method is thus useful for phenomic studies aimed at finding the genetic basis behind root system architecture and the subsequent development of more productive crops.