Thematische Bibliographien / Skeleton segmentation

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Auswahl der wissenschaftlichen Literatur zum Thema „Skeleton segmentation“

Autor: Grafiati

Veröffentlicht am 25. Juni 2021

Zuletzt aktualisiert am 17. Februar 2022

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Zeitschriftenartikel zum Thema "Skeleton segmentation"

TAKUMA, Naoki, Koichiro DEGUCHI, and Iwao MORISHITA. "Image Figure Segmentation Using Morphological Skeleton." Transactions of the Society of Instrument and Control Engineers 29, no. 11 (1993): 1361–68. http://dx.doi.org/10.9746/sicetr1965.29.1361.

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Lee, Jonha, Dong-Wook Kim, Chee Won, and Seung-Won Jung. "Graph Cut-Based Human Body Segmentation in Color Images Using Skeleton Information from the Depth Sensor." Sensors 19, no. 2 (2019): 393. http://dx.doi.org/10.3390/s19020393.

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Segmentation of human bodies in images is useful for a variety of applications, including background substitution, human activity recognition, security, and video surveillance applications. However, human body segmentation has been a challenging problem, due to the complicated shape and motion of a non-rigid human body. Meanwhile, depth sensors with advanced pattern recognition algorithms provide human body skeletons in real time with reasonable accuracy. In this study, we propose an algorithm that projects the human body skeleton from a depth image to a color image, where the human body regio

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Moreno-Avendano, Santiago, Daniel Mejia-Parra, and Oscar Ruiz-Salguero. "Triangle mesh skeletonization using non-deterministic voxel thinning and graph spectrum segmentation." MATEC Web of Conferences 336 (2021): 02030. http://dx.doi.org/10.1051/matecconf/202133602030.

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In the context of shape processing, the estimation of the medial axis is relevant for the simplification and re-parameterization of 3D bodies. The currently used methods are based on (1) General fields, (2) Geometric methods and (3) voxel-based thinning. They present shortcomings such as (1) overrepresentation and non-smoothness of the medial axis due to high frequency nodes and (2) biased-skeletons due to skewed thinning. To partially overcome these limitations, this article presents a non-deterministic algorithm for the estimation of the 1D skeleton of triangular B-Reps or voxel-based body r

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Grun, Tobias B., and James H. Nebelsick. "Structural design of the minute clypeasteroid echinoid Echinocyamus pusillus." Royal Society Open Science 5, no. 5 (2018): 171323. http://dx.doi.org/10.1098/rsos.171323.

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The clypeasteroid echinoid skeleton is a multi-plated, light-weight shell construction produced by biomineralization processes. In shell constructions, joints between individual elements are considered as weak points, yet these echinoid skeletons show an extensive preservation potential in both Recent and fossil environments. The remarkable strength of the test is achieved by skeletal reinforcement structures and their constructional layouts. Micro-computed tomography and scanning electron microscopy are used for microstructural and volumetric analyses of the echinoid's skeleton. It is shown t

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Sun, Xiaopeng, J. Pan, and Xiaopeng Wei. "3D mesh skeleton extraction using prominent segmentation." Computer Science and Information Systems 7, no. 1 (2010): 63–74. http://dx.doi.org/10.2298/csis1001063s.

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Skeleton of 3D mesh is a fundamental shape feature, and is useful for shape description and other many applications in 3D Digital Geometry Processing. This paper presents a novel skeleton extraction algorithm based on feature point and core extraction by the Multidimensional scaling (MDS) transformation. The algorithm first straights the folded prominent branch up, as well as the prominent shape feature points of mesh are computed, a meaningful segmentation is applied under the direction of feature points. The Node-ring of all segmented components is defined by discrete geodesic path on mesh s

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CHENG, JIN-CHANG, and HON-SON DON. "SEGMENTATION OF BILEVEL IMAGES USING MATHEMATICAL MORPHOLOGY." International Journal of Pattern Recognition and Artificial Intelligence 06, no. 04 (1992): 595–628. http://dx.doi.org/10.1142/s0218001492000321.

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This paper presents the results of a study on the use of morphological skeleton transformation to segment gray-scale images into bilevel images. When a bilevel image (such as printed texts and machine tools) is digitized, the result is a gray-scale image due to the point spread function of digitizer, non-uniform illumination and noise. Our method can recover the original bilevel image from the gray-scale image. The theoretical basis of the algorithm is the physical structure of the skeleton set. A connectivity property of the gray-scale skeleton transformation is used to separate and remove th

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Li Renzhong, 李仁忠, 刘哲闻 Liu Zhewen, and 刘阳阳 Liu Yangyang. "Segmentation Algorithm Based on Point Cloud Skeleton." Laser & Optoelectronics Progress 56, no. 22 (2019): 221102. http://dx.doi.org/10.3788/lop56.221102.

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Singh, M., and J. Feldman. "Skeleton-based segmentation of shapes into parts." Journal of Vision 8, no. 6 (2010): 719. http://dx.doi.org/10.1167/8.6.719.

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Grosgeorge, Damien, Caroline Petitjean, Bernard Dubray, and Su Ruan. "Esophagus Segmentation from 3D CT Data Using Skeleton Prior-Based Graph Cut." Computational and Mathematical Methods in Medicine 2013 (2013): 1–6. http://dx.doi.org/10.1155/2013/547897.

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The segmentation of organs at risk in CT volumes is a prerequisite for radiotherapy treatment planning. In this paper, we focus on esophagus segmentation, a challenging application since the wall of the esophagus, made of muscle tissue, has very low contrast in CT images. We propose in this paper an original method to segment in thoracic CT scans the 3D esophagus using a skeleton-shape model to guide the segmentation. Our method is composed of two steps: a 3D segmentation by graph cut with skeleton prior, followed by a 2D propagation. Our method yields encouraging results over 6 patients.

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Kontges, G., and A. Lumsden. "Rhombencephalic neural crest segmentation is preserved throughout craniofacial ontogeny." Development 122, no. 10 (1996): 3229–42. http://dx.doi.org/10.1242/dev.122.10.3229.

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To investigate the influence of hindbrain segmentation on craniofacial patterning we have studied the long term fate of neural crest (NC) subpopulations of individual rhombomeres (r), using quail-chick chimeras. Mapping of all skeletal and muscle connective tissues developing from these small regions revealed several novel features of the cranial neural crest. First, the mandibular arch skeleton has a composite origin in which the proximal elements are r1+r2 derived, whereas more distal ones are exclusively midbrain derived. The most proximal region of the lower jaw is derived from second arch

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Dissertationen zum Thema "Skeleton segmentation"

Hedström, Anders. "Automatic Segmentation of Skeleton in Whole-Body MR Images." Thesis, Uppsala universitet, Institutionen för informationsteknologi, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-211221.

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Magnetic Resonance Imaging(MRI) has developed as a widespread technique to examine various body parts and diagnose a wide range of diseases. MRI can often be superior to other imaging techniques such as Computed Tomography(CT) since it does not use ionizing radiation and can give a clearer image of soft tissue. As MRI becomes a more important part in medicine the demands on software to analyse the images and extract useful information increases. Today medical image analysis can be used to localise tumours, measure brain substance and to isolate specific organs. Although much has happened in th

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Lidayová, Kristína. "Fast Methods for Vascular Segmentation Based on Approximate Skeleton Detection." Doctoral thesis, Uppsala universitet, Avdelningen för visuell information och interaktion, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-318796.

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Modern medical imaging techniques have revolutionized health care over the last decades, providing clinicians with high-resolution 3D images of the inside of the patient's body without the need for invasive procedures. Detailed images of the vascular anatomy can be captured by angiography, providing a valuable source of information when deciding whether a vascular intervention is needed, for planning treatment, and for analyzing the success of therapy. However, increasing level of detail in the images, together with a wide availability of imaging devices, lead to an urgent need for automated t

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Pérez, Rocha Ana Laura. "Segmentation and Line Filling of 2D Shapes." Thèse, Université d'Ottawa / University of Ottawa, 2013. http://hdl.handle.net/10393/23676.

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The evolution of technology in the textile industry reached the design of embroidery patterns for machine embroidery. In order to create quality designs the shapes to be embroidered need to be segmented into regions that define different parts. One of the objectives of our research is to develop a method to automatically segment the shapes and by doing so making the process faster and easier. Shape analysis is necessary to find a suitable method for this purpose. It includes the study of different ways to represent shapes. In this thesis we focus on shape representation through its skeleton.

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HE, LEI. "A COMPARISON OF DEFORMABLE CONTOUR METHODS AND MODEL BASED APPROACH USING SKELETON FOR SHAPE RECOVERY FROM IMAGES." University of Cincinnati / OhioLINK, 2003. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1059746287.

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Belbaisi, Adham. "Deep Learning-Based Skeleton Segmentation for Analysis of Bone Marrow and Cortical Bone in Water-Fat Magnetic Resonance Imaging." Thesis, KTH, Skolan för kemi, bioteknologi och hälsa (CBH), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-297528.

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A major health concern for subjects with diabetes is weaker bones and increased fracture risk. Current clinical assessment of the bone strength is performed by measuring Bone Mineral Density (BMD), where low BMD-values are associated with an increased risk of fracture. However, subjects with Type 2 Diabetes (T2D) have been shown to have normal or higher BMD-levels compared to healthy controls, which does not reflect the recognized bone fragility among diabetics. Thus, there is need for more research about diabetes-related bone fragility to find other factors of impaired bone health. One potent

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Limkhaitir, Mohamed Mahmoud. "Modélisation des formes volumiques à partir d'images tomographiques 3D : application à la Caractérisation de l'espace poral du sol." Thesis, Paris 6, 2014. http://www.theses.fr/2014PA066556.

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Nous présentations dans ce travail une méthode de représentation des formes volumiques 3D complexes. Nous dé nissons une forme volumique 3D par un ensemble de voxels extrait d'un traitement d'images Tomographiques 3D. cet ensemble est définit par sa fonction indicatrice. Notre objectif est le calcul d'une approximation analytique continue par morceau, compact, stable et robuste de la forme initiale, qui conserve ses propriétés topologiques et géométriques. Nous proposons une description de la forme par un ensemble minimum de boules incluses dans la forme et recouvrant son squelette. Nous démon

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Erdem, Mehmet Erkut. "Simultaneous Bottom-up/top-down Processing In Early And Mid Level Vision." Phd thesis, METU, 2008. http://etd.lib.metu.edu.tr/upload/12610167/index.pdf.

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The prevalent view in computer vision since Marr is that visual perception is a data-driven bottom-up process. In this view, image data is processed in a feed-forward fashion where a sequence of independent visual modules transforms simple low-level cues into more complex abstract perceptual units. Over the years, a variety of techniques has been developed using this paradigm. Yet an important realization is that low-level visual cues are generally so ambiguous that they could make purely bottom-up methods quite unsuccessful. These ambiguities cannot be resolved without taking account of high-

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Gopalan, Sowmya. "Estimating Columnar Grain Size in Steel-Weld Images using Image Processing Techniques." The Ohio State University, 2009. http://rave.ohiolink.edu/etdc/view?acc_num=osu1250621610.

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Essafi, Salma. "3D Knowledge-based Segmentation Using Sparse Hierarchical Models : contribution and Applications in Medical Imaging." Phd thesis, Ecole Centrale Paris, 2010. http://tel.archives-ouvertes.fr/tel-00534805.

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CETTE thèse est consacrée à la conception d'un système d'aide au diagnostic dédiéau muscle squelettique humain. Au cours du premier volet de ce manuscrit nousproposons une nouvelle représentation basée sur les modèles parcimonieux dans le cadrede la segmentation d'Images de Résonances Magnétiques (IRM) T1 du muscle squelettiquedu mollet. Notre méthode Sparse Shape Model/ Modèle de Formes Parcimonieux(MFP), apprend un modèle statistique de formes et de textures locales annoté et réussità en tirer une représentation réduite afin de reconstruire le mécanisme musculaire sur unexemple test. Dans la

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Karlsson, Edlund Patrick. "Methods and models for 2D and 3D image analysis in microscopy, in particular for the study of muscle cells." Doctoral thesis, Uppsala : Acta Universitatis Upsaliensis, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-9201.

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Bücher zum Thema "Skeleton segmentation"

F, Nielsen Poul M., Miller Karol, and SpringerLink (Online service), eds. Computational Biomechanics for Medicine: Soft Tissues and the Musculoskeletal System. Springer Science+Business Media, LLC, 2011.

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Burton, Derek, and Margaret Burton. The skeleton, support and movement. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198785552.003.0003.

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Buoyancy largely supports fish, reducing the role of the skeleton, which functions as an attachment for muscle involved in movement and in protection, as exoskeleton (scales, scutes, bony plates) and as endoskeleton (vertebral column, skull). The general organization of fish skeletons and their component parts are described, as well as bone and cartilage. The interesting occurrence of acellular bone, additional to cellular bone, in teleosts is considered. Fish show metameric segmentation with myotomes on either side of the vertebral column, the latter acting as a compression strut, preventing

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Buchteile zum Thema "Skeleton segmentation"

Gaillard, Mathieu, Chenyong Miao, James Schnable, and Bedrich Benes. "Sorghum Segmentation by Skeleton Extraction." In Computer Vision – ECCV 2020 Workshops. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-65414-6_21.

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Feng, Cong, Andrei C. Jalba, and Alexandru C. Telea. "Part-Based Segmentation by Skeleton Cut Space Analysis." In Lecture Notes in Computer Science. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-18720-4_51.

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Lovato, Christian, Umberto Castellani, and Andrea Giachetti. "Automatic Segmentation of Scanned Human Body Using Curve Skeleton Analysis." In Computer Vision/Computer Graphics CollaborationTechniques. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-01811-4_4.

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Yangel, Boris, and Dmitry Vetrov. "Image Segmentation with a Shape Prior Based on Simplified Skeleton." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-23094-3_18.

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Wu, Zonghan, Baochang Zhang, Jun Yang, Na Li, and Shoujun Zhou. "Segmentation of Arteriovenous Malformation Based on Weighted Breadth-First Search of Vascular Skeleton." In Communications in Computer and Information Science. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-39343-4_25.

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Rabatel, Gilles, Anne-Gaëlle Manh, Marie-José Aldon, and Bernard Bonicelli. "Skeleton-Based Shape Models with Pressure Forces: Application to Segmentation of Overlapping Leaves." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/3-540-45129-3_22.

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Ng, Kok-Why, Abdullah Junaidi, and Sew-Lai Ng. "Semi-automatic Segmentation of 3D Point Clouds Skeleton without Explicit Computation for Critical Points." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-32695-0_73.

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Shankar, Venkatesh Gauri, Bali Devi, Ujwal Sachdeva, and Harsh Harsola. "Real-Time Human Body Tracking System for Posture and Movement Using Skeleton-Based Segmentation." In Micro-Electronics and Telecommunication Engineering. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-33-4687-1_48.

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Xie, Wenjie, Renato Perucchio, David Sedmera, and Robert P. Thompson. "Topological Segmentation and Smoothing of Discrete Curve Skeletons." In Computer-Aided Intelligent Recognition Techniques and Applications. John Wiley & Sons, Ltd, 2005. http://dx.doi.org/10.1002/0470094168.ch20.

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Röhrle, O., H. Köstler, and M. Loch. "Segmentation of Skeletal Muscle Fibres for Applications in Computational Skeletal Muscle Mechanics." In Computational Biomechanics for Medicine. Springer New York, 2011. http://dx.doi.org/10.1007/978-1-4419-9619-0_12.

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Konferenzberichte zum Thema "Skeleton segmentation"

"Skeleton-Based Shape Segmentation." In International Workshop on Image Mining Theory and Applications. SciTePress - Science and and Technology Publications, 2009. http://dx.doi.org/10.5220/0001963500840092.

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Neubauer, Andre, and Rainer Wegenkittl. "Skeleton-based myocardium segmentation." In Electronic Imaging 2003, edited by Robert F. Erbacher, Philip C. Chen, Jonathan C. Roberts, Matti T. Groehn, and Katy Boerner. SPIE, 2003. http://dx.doi.org/10.1117/12.473945.

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Reniers, Dennie, and Alexandru Telea. "Skeleton-based Hierarchical Shape Segmentation." In IEEE International Conference on Shape Modeling and Applications 2007 (SMI '07). IEEE, 2007. http://dx.doi.org/10.1109/smi.2007.33.

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Cai, Ling, Fengna Wang, Valentin Enescu, and Hichem Sahli. "Object Segmentation Based on Contour-Skeleton Duality." In 2014 22nd International Conference on Pattern Recognition (ICPR). IEEE, 2014. http://dx.doi.org/10.1109/icpr.2014.438.

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de Belen, Ryan Anthony J., and Rowel O. Atienza. "Automatic skeleton generation using hierarchical mesh segmentation." In SA '16: SIGGRAPH Asia 2016. ACM, 2016. http://dx.doi.org/10.1145/2992138.2992150.

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Jacques Junior, Julio C. S., Claudio R. Jung, and Soraia R. Musse. "Skeleton-based human segmentation in still images." In 2012 19th IEEE International Conference on Image Processing (ICIP 2012). IEEE, 2012. http://dx.doi.org/10.1109/icip.2012.6466815.

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Manolas, Iason, Aris S. Lalos, and Konstantinos Moustakas. "Parallel 3D Skeleton Extraction Using Mesh Segmentation." In 2018 International Conference on Cyberworlds (CW). IEEE, 2018. http://dx.doi.org/10.1109/cw.2018.00041.

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Yu, Donggang, Tuan D. Pham, Hong Yan, et al. "Segmentation and Reconstruction of Cultured Neuron Skeleton." In COMPUTATIONAL MODELS FOR LIFE SCIENCES/CMLS '07. AIP, 2007. http://dx.doi.org/10.1063/1.2816626.

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Wshah, Safwan, Zhixin Shi, and Venu Govindaraju. "Segmentation of Arabic Handwriting Based on both Contour and Skeleton Segmentation." In 2009 10th International Conference on Document Analysis and Recognition. IEEE, 2009. http://dx.doi.org/10.1109/icdar.2009.152.

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Tal, Ayellet. "Mesh Segmentation for CAD Applications." In ASME 2008 9th Biennial Conference on Engineering Systems Design and Analysis. ASMEDC, 2008. http://dx.doi.org/10.1115/esda2008-59565.

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Segmentation of meshes has received a lot of attention in recent years, due to its growing number of applications. In this paper, we discuss properties that have been used in the literature to evaluate segmentation algorithms. Then, we describe some applications of segmentation in CAD. For each application, we review one of our segmentation algorithms that is suitable for the problem. We focus on four applications: modeling by example, shape-based retrieval, skeleton extraction, and paper crafting.

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