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Relevant bibliographies by topics / And Fast Level Set Method

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Academic literature on the topic 'And Fast Level Set Method'

Author: Grafiati

Published: 5 June 2025

Last updated: 15 July 2025

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Journal articles on the topic "And Fast Level Set Method"

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Tsuji, T., C. Jasnoch, R. Kurazume, and T. Hasegawa. "Tracking Multiple Objects Using the Fast Level Set Method." Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec) 2004 (2004): 202. http://dx.doi.org/10.1299/jsmermd.2004.202_4.

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Iwashita, Y., T. Yamasaki, R. Kurazume, and T. Hasegawa. "Implementation fo Fast Level Set Method on a PC-cluster." Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec) 2004 (2004): 134. http://dx.doi.org/10.1299/jsmermd.2004.134_2.

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Peng, Danping, Barry Merriman, Stanley Osher, Hongkai Zhao, and Myungjoo Kang. "A PDE-Based Fast Local Level Set Method." Journal of Computational Physics 155, no. 2 (1999): 410–38. http://dx.doi.org/10.1006/jcph.1999.6345.

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Adalsteinsson, David, and James A. Sethian. "A Fast Level Set Method for Propagating Interfaces." Journal of Computational Physics 118, no. 2 (1995): 269–77. http://dx.doi.org/10.1006/jcph.1995.1098.

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Isakov, Victor, Shingyu Leung, and Jianliang Qian. "A Fast Local Level Set Method for Inverse Gravimetry." Communications in Computational Physics 10, no. 4 (2011): 1044–70. http://dx.doi.org/10.4208/cicp.100710.021210a.

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AbstractWe propose a fast local level set method for the inverse problem of gravimetry. The theoretical foundation for our approach is based on the following uniqueness result: if an open set D is star-shaped or x3-convex with respect to its center of gravity, then its exterior potential uniquely determines the open set D. To achieve this purpose constructively, the first challenge is how to parametrize this open set D as its boundary may have a variety of possible shapes. To describe those different shapes we propose to use a level-set function to parametrize the unknown boundary of this open set. The second challenge is how to deal with the issue of partial data as gravimetric measurements are only made on a part of a given reference domain Ω. To overcome this difficulty we propose a linear numerical continuation approach based on the single layer representation to find potentials on the boundary of some artificial domain containing the unknown set D. The third challenge is how to speed up the level set inversion process. Based on some features of the underlying inverse gravimetry problem such as the potential density being constant inside the unknown domain, we propose a novel numerical approach which is able to take advantage of these features so that the computational speed is accelerated by an order of magnitude. We carry out numerical experiments for both two- and three-dimensional cases to demonstrate the effectiveness of the new algorithm.

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Yang, Xi, Xinbo Gao, Dacheng Tao, and Xuelong Li. "Improving Level Set Method for Fast Auroral Oval Segmentation." IEEE Transactions on Image Processing 23, no. 7 (2014): 2854–65. http://dx.doi.org/10.1109/tip.2014.2321506.

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Serikawa, Seiichi, Huimin Lu, Yujie Li, Huiliang Xu, and Yun Li. "Underwater image segmentation based on fast level set method." International Journal of Computational Science and Engineering 19, no. 4 (2019): 562. http://dx.doi.org/10.1504/ijcse.2019.10023457.

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Li, Yujie, Huiliang Xu, Yun Li, Huimin Lu, and Seiichi Serikawa. "Underwater image segmentation based on fast level set method." International Journal of Computational Science and Engineering 19, no. 4 (2019): 562. http://dx.doi.org/10.1504/ijcse.2019.101879.

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Suba�i�, Marko. "Level Set Methods and Fast Marching Methods." Journal of Computing and Information Technology 11, no. 1 (2003): 79. http://dx.doi.org/10.2498/cit.2003.01.07.

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Zhu, Fuping, and Jie Tian. "Modified fast marching and level set method for medical image segmentation." Journal of X-Ray Science and Technology: Clinical Applications of Diagnosis and Therapeutics 11, no. 4 (2003): 193–204. http://dx.doi.org/10.3233/xst-2003-00081.

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In this paper, an interactive segmentation method that combines fast marching and level set method is proposed. Level set segmentation involves solving the energy-based active contour minimization problems by the computation of geodesics or minimal distance curves. First, by selecting the seed point, the fast marching method is used to extract rough boundaries of the interested object. We modified the traditional fast marching method to capture the weak edges by introducing watershed transform. Then, the contour obtained from the fast marching method mentioned above is regarded as an initialization and the level set method is used to finely tune the contour. The algorithm is demonstrated on some medical images: segmentation of knee tissues in CT image and segmentation of brain tissues in MR image. The results show that this method can remove the small regions obtained from fast marching method and converge the desired boundary.

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Dissertations / Theses on the topic "And Fast Level Set Method"

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Hearn, Jonathan. "COMPETITIVE MEDICAL IMAGE SEGMENTATION WITH THE FAST MARCHING METHOD." Case Western Reserve University School of Graduate Studies / OhioLINK, 2008. http://rave.ohiolink.edu/etdc/view?acc_num=case1201033602.

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Lo, Shin-en. "A Fire Simulation Model for Heterogeneous Environments Using the Level Set Method." Scholarship @ Claremont, 2012. http://scholarship.claremont.edu/cgu_etd/72.

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Wildfire hazard and its destructive consequences have become a growing issue around the world especially in the context of global warming. An effective and efficient fire simulation model will make it possible to predict the fire spread and assist firefighters in the process of controlling the damage and containing the fire area. Simulating wildfire spread remains challenging due to the complexity of fire behaviors. The raster-based method and the vector-based method are two major approaches that allow one to perform computerized fire spread simulation. In this thesis, we present a scheme we have developed that utilizes a level set method to build a fire spread simulation model. The scheme applies the strengths and overcomes some of the shortcomings of the two major types of simulation method. We store fire data and local rules at cells. Instead of calculating which are the next ignition points cell by cell, we apply Huygens' principle and elliptical spread assumption to calculate the direction and distance of the expanding fire by the level set method. The advantage to storing data at cells is that it makes our simulation model more suitable for heterogeneous fuel and complex topographic environment. Using a level set method for our simulation model makes it possible to overcome the crossover problem. Another strength of the level set method is its continuous data processing. Applying the level set method in the simulation models, we need fewer vector points than raster cells to produce a more realistic fire shape. We demonstrate this fire simulation model through two implementations using narrow band level set method and fast marching method. The simulated results are compared to the real fire image data generated from Troy and Colina fires. The simulation data are then studied and compared. The ultimate goal is to apply this simulation model to the broader picture to better predict different types of fires such as crown fire, spotting fires, etc.

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Xu, Bin. "Fast Path Planning in Uncertain Environments: Theory and Experiments." Diss., Virginia Tech, 2009. http://hdl.handle.net/10919/29734.

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This dissertation addresses path planning for an autonomous vehicle navigating in a two dimensional environment for which an a priori map is inaccurate and for which the environment is sensed in real-time. For this class of application, planning decisions must be made in real-time. This work is motivated by the need for fast autonomous vehicles that require planning algorithms to operate as quickly as possible. In this dissertation, we first study the case in which there are only static obstacles in the environment. We propose a hybrid receding horizon control path planning algorithm that is based on level-set methods. The hybrid method uses global or local level sets in the formulation of the receding horizon control problem. The decision to select a new level set is made based on certain matching conditions that guarantee the optimality of the path. We rigorously prove sufficient conditions that guarantee that the vehicle will converge to the goal as long as a path to the goal exists. We then extend the proposed receding horizon formulation to the case when the environment possesses moving obstacles. Since all of the results in this dissertation are based on level-set methods, we rigorously investigate how level sets change in response to new information locally sensed by a vehicle. The result is a dynamic fast marching algorithm that usually requires significantly less computation that would otherwise be the case. We demonstrate the proposed dynamic fast marching method in a successful field trial for which an autonomous surface vehicle navigated four kilometers through a riverine environment.<br>Ph. D.

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MUKHERJEE, NANDINI. "3D DEFORMABLE CONTOUR SURFACE RECONSTRUCTION: AN OPTIMIZED ESTMATION METHOD." University of Cincinnati / OhioLINK, 2004. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1078255615.

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Chen, Weitao. "Fast Sweeping Methods for Steady State Hyperbolic Conservation Problems and Numerical Applications for Shape Optimization and Computational Cell Biology." The Ohio State University, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=osu1366279632.

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Hui, Fei. "Visual Tracking of Deformation and Classification of Object Elasticity with Robotic Hand Probing." Thesis, Université d'Ottawa / University of Ottawa, 2017. http://hdl.handle.net/10393/36477.

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Performing tasks with a robotic hand often requires a complete knowledge of the manipulated object, including its properties (shape, rigidity, surface texture) and its location in the environment, in order to ensure safe and efficient manipulation. While well-established procedures exist for the manipulation of rigid objects, as well as several approaches for the manipulation of linear or planar deformable objects such as ropes or fabric, research addressing the characterization of deformable objects occupying a volume remains relatively limited. The fundamental objectives of this research are to track the deformation of non-rigid objects under robotic hand manipulation using RGB-D data, and to automatically classify deformable objects as either rigid, elastic, plastic, or elasto-plastic, based on the material they are made of, and to support recognition of the category of such objects through a robotic probing process in order to enhance manipulation capabilities. The goal is not to attempt to formally model the material of the object, but rather employ a data-driven approach to make decisions based on the observed properties of the object, capture implicitly its deformation behavior, and support adaptive control of a robotic hand for other research in the future. The proposed approach advantageously combines color image and point cloud processing techniques, and proposes a novel combination of the fast level set method with a log-polar mapping of the visual data to robustly detect and track the contour of a deformable object in a RGB-D data stream. Dynamic time warping is employed to characterize the object properties independently from the varying length of the detected contour as the object deforms. The research results demonstrate that a recognition rate over all categories of material of up to 98.3% is achieved based on the detected contour. When integrated in the control loop of a robotic hand, it can contribute to ensure stable grasp, and safe manipulation capability that will preserve the physical integrity of the object.

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Ervik, Åsmund. "The Local Level-Set Extraction Method for Robust Calculation of Geometric Quantities in the Level-Set Method." Thesis, Norges teknisk-naturvitenskapelige universitet, Institutt for fysikk, 2012. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-19429.

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The level-set method is an implicit interface capturing method that can be used in two or more dimensions. The method is popular e.g. in computer graphics, and as here, in simulations of two-phase flow. The motivation for the simulations performed here is to obtain a better understanding of the complex two-phase flow phenomena ocurring in heat exchangers used for liquefaction of natural gas, including the study of droplet-film interactions and coalescence.One of the main advantages of the level-set method is that it handles changes in the interface topology in a natural way. In the present work, the calculation of the curvature and normal vectors of an interface represented by the level-set method is considered. The curvature and normal vectors are usually calculated using central-difference stencils, but this standard method fails when the interface undergoesa topological change, e.g. when two droplets collide and merge. Several methodshave previously been developed to handle this problem. In the present work,a new method is presented, which is a development on existing methods. The newmethod handles more general cases than previous methods. In contrast to someprevious methods, the present method retains the implicit formulation and can easily be extended to three-dimensional simulations, as demonstrated in this work.Briefly, the new method consists in extracting one or more local level sets forbodies close to the grid point considered, reinitializing these local level setsto remove kinks, and using these to calculate the curvature and normal vector atthe grid point considered. For the curvature, multiple values are averaged,while for the normal vector, the one corresponding to the closest interface isselected.With this new method, several two-phase flow simulations are performed that arerelevant for understanding the liquefaction of natural gas. The new methodenables simulations that are more general than previous ones. A two-dimensionalsimulation was performed of a 0.6 mm diameter methanol droplet falling through air and merging with a deep pool of methanol. The new method gave good results in this case, but unphysical oscillations in the pressure field rendered this result unsuitablefor comparison with experimental results.Several similar cases with significantly lower density differences between thetwo fluids were also considered; in these cases, the pressure field behavedphysically, but the results are less applicable to the understanding of naturalgas liquefication, and better suited for validation of the new method. Inparticular, an axisymmetric simulation of a 0.11 mm diameter water droplet in decanemerging with a deep pool of water has been considered. The results of thissimulation show a very close agreement with experimental data. Attempts werealso made to simulate a larger droplet, but in this case finer grids were neededthan what could be achieved here due to the computational time cost of gridrefinement. Purely geometrical results are also presented in order to validate the results of the new method, and three-dimensional results are given for a static interface configuration, demonstrating that the method is easily extended to higher dimensions.

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Wagstaff, Harry. "From high level architecture descriptions to fast instruction set simulators." Thesis, University of Edinburgh, 2015. http://hdl.handle.net/1842/14162.

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As computer systems become increasingly complex and diverse, so too do the architectures they implement. This leads to an increase in complexity in the tools used to design new hardware and software. One particularly important tool in hardware and software design is the Instruction Set Simulator, which is used to prototype new architectures and hardware features, verify hardware, and test and debug software. Many Architecture Description Languages exist which facilitate the description of new architectural or hardware features, and generate a tools such as simulators. However, these typically suffer from poor performance, are difficult to test effectively, and may be limited in functionality. This thesis considers three objectives when developing Instruction Set Simulators: performance, correctness, and completeness, and presents techniques which contribute to each of these. Performance is obtained by combining Dynamic Binary Translation techniques with a novel analysis of high level architecture descriptions. This makes use of partial evaluation techniques in order to both improve the translation system, and to improve the quality of the translated code, leading a performance improvement of over 2.5x compared to a naïve implementation. This thesis also presents techniques which contribute to the correctness objective. Each possible behaviour of each described instruction is used to guide the generation of a test case. Constraint satisfaction techniques are used to determine the necessary instruction encoding and context for each behaviour to be produced. It is shown that this is a significant improvement over benchmark-driven testing, and this technique has led to the discovery of several bugs and inconsistencies in multiple state of the art instruction set simulators. Finally, several challenges in ‘Full System’ simulation are addressed, contributing to both the performance and completeness objectives. Full System simulation generally carries significant performance costs compared with other simulation strategies. Crucially, instructions which access memory require virtual to physical address translation and can now cause exceptions. Both of these processes must be correctly and efficiently handled by the simulator. This thesis presents novel techniques to address this issue which provide up to a 1.65x speedup over a state of the art solution.

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Johansson, John. "Efficient implementation of the Particle Level Set method." Thesis, Linköping University, Media and Information Technology, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-59579.

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<p>The Particle Level set method is a successful extension to Level set methods to improve thevolume preservation in fluid simulations. This thesis will analyze how sparse volume data structures can be used to store both the signed distance function and the particles in order to improve access speed and memory efficiency. This Particle Level set implementation will be evaluated against Digital Domains current Particle Level set implementation. Different degrees of quantization will be used to implement particle representations with varying accuracy. These particles will be tested and both visual results and error measurments will be presented. The sparse volume data structures DB-Grid and Field3D will be evaluated in terms of speed and memory efficiency.</p>

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Lim, Poay Hoon. "Improved level set method for spinal vertebrae segmentation." Thesis, University of Nottingham, 2013. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.594415.

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Accurate segmemation of spinal vertebrae is important in the study of spinal related disease or disorders such as vertebral fractures. Identifying the severity of fractures and understanding its cause will help physicians determine the most effective pharmacological treatments and clinical management strategies for spinal disorders. Detection and segmentation are the crucial steps towards this quantitative framework. Although these quantitative image analysis techniques have received increasing interest recently, accurate detection and segmentation methods are still lacking. The complexity of vertebrae shapes, gaps in the cortical bone, internal boundaries, as well as the noisy. incomplete or missing information from the medical images have undoubtedly increased the challenge. Level set methods are effective for image segmentation. They are well-known for their ability to handle abrupt topological changes. However, the methods suffer from limitations such as slow convergence and leaking problems. As such, over the past two decades, the original level set method has evolved in many directions, including integration of prior shape models into the segmentation framework. For highly challenging medical images, incorporating prior shape into the segmentation framework have shown great success in recent years. In this work, a new shape model and an associated energy for level set segmentation is proposed. The proposed shape model presents a new dimension to extract local shape parameter directly from the shape model, which is different from previous work that focused on an indirect manner of feature extractions and in global sense. For the 2D and 3D segmentation of spinal vertebrae, a new segmentation framework combining the use of Willmore functional and kernel density estimation is proposed. While the kernel density estimator provide a dissimilarity measure with the shape prior during the level set evolution, the Willmore energy helps to regularize and smoothen the surface in the process. The introduction of Willmore functional into the 3D segmentation framework has solved the commonly encountered irregularity problem on extracted surface. Experimental results clearly demonstrate the feasibility of the proposed framework when tested on CT images of spinal vertebrae. The ultimate goal of this work is to provide a quantitative platform for efficient and accurate diagnosis of spinal disorder related diseases.

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Books on the topic "And Fast Level Set Method"

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Albert, Sethian James, ed. Level set methods and fast marching methods: Evolving interfaces in computational geometry, fluid mechanics, computer vision, and materials science. 2nd ed. Cambridge University Press, 1999.

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Suri, Jasjit S., and Ayman S. El-Baz. Level Set Method in Medical Imaging Segmentation. Taylor & Francis Group, 2019.

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Suri, Jasjit S., and Ayman El-Baz. Level Set Method in Medical Imaging Segmentation. Taylor & Francis Group, 2019.

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Suri, Jasjit S., and Ayman El-Baz. Level Set Method in Medical Imaging Segmentation. Taylor & Francis Group, 2019.

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Suri, Jasjit S., and Ayman El-Baz. Level Set Method in Medical Imaging Segmentation. Taylor & Francis Group, 2019.

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Suri, Jasjit S., and Ayman El-Baz. Level Set Method in Medical Imaging Segmentation. Taylor & Francis Group, 2019.

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Level Set Method in Medical Imaging Segmentation. Taylor & Francis Group, 2023.

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Hill, McGraw. Fast Track Reading, Complete Level 5 Set. McGraw-Hill Education, 2003.

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Hill, McGraw. Fast Track Reading, Complete Level 3 Set. McGraw-Hill Education, 2003.

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Hill, McGraw. Fast Track Reading, Complete Level 6 Set. McGraw-Hill Education, 2003.

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Book chapters on the topic "And Fast Level Set Method"

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Andersson, Thord, Gunnar Läthén, Reiner Lenz, and Magnus Borga. "A Fast Optimization Method for Level Set Segmentation." In Image Analysis. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-02230-2_41.

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Christiansen, Oddvar, and Xue-Cheng Tai. "Fast Implementation of Piecewise Constant Level Set Methods." In Image Processing Based on Partial Differential Equations. Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-33267-1_16.

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Liang, Ruquan, and Nobuyuki Satofuka. "Numerical Simulation of Droplet and Bubble Flows Using Fast Level Set Method." In Computational Fluid Dynamics 2000. Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/978-3-642-56535-9_111.

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Thida, Myo, Kap Luk Chan, and How-Lung Eng. "An Improved Real-Time Contour Tracking Algorithm Using Fast Level Set Method." In Advances in Image and Video Technology. Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11949534_70.

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Puranik, Minal M., and Shobha Krishnan. "Segmentation of Image Using Watershed and Fast Level Set Methods." In Information Technology and Mobile Communication. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-20573-6_40.

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Sethian, J. A. "Advances in Fast Marching and Level Set Methods for Propagating Interfaces." In Hyperbolic Problems: Theory, Numerics, Applications. Birkhäuser Basel, 1999. http://dx.doi.org/10.1007/978-3-0348-8724-3_36.

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Sethian, J. A. "A review of level set and fast marching methods for image processing." In Modern Methods in Scientific Computing and Applications. Springer Netherlands, 2002. http://dx.doi.org/10.1007/978-94-010-0510-4_10.

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Juniper, Matthew P. "Machine Learning for Thermoacoustics." In Lecture Notes in Energy. Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-16248-0_11.

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AbstractThis chapter demonstrates three promising ways to combine machine learning with physics-based modelling in order to model, forecast, and avoid thermoacoustic instability. The first method assimilates experimental data into candidate physics-based models and is demonstrated on a Rijke tube. This uses Bayesian inference to select the most likely model. This turns qualitatively-accurate models into quantitatively-accurate models that can extrapolate, which can be combined powerfully with automated design. The second method assimilates experimental data into level set numerical simulations of a premixed bunsen flame and a bluff-body stabilized flame. This uses either an Ensemble Kalman filter, which requires no prior simulation but is slow, or a Bayesian Neural Network Ensemble, which is fast but requires prior simulation. This method deduces the simulations’ parameters that best reproduce the data and quantifies their uncertainties. The third method recognises precursors of thermoacoustic instability from pressure measurements. It is demonstrated on a turbulent bunsen flame, an industrial fuel spray nozzle, and full scale aeroplane engines. With this method, Bayesian Neural Network Ensembles determine how far each system is from instability. The trained BayNNEs out-perform physics-based methods on a given system. This method will be useful for practical avoidance of thermoacoustic instability.

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Osher, Stanley, and Ronald Fedkiw. "Particle Level Set Method." In Applied Mathematical Sciences. Springer New York, 2003. http://dx.doi.org/10.1007/0-387-22746-6_9.

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Xiang, Yang, and David J. Srolovitz. "Level Set Dislocation Dynamics Method." In Handbook of Materials Modeling. Springer Netherlands, 2005. http://dx.doi.org/10.1007/1-4020-3286-2_119.

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Conference papers on the topic "And Fast Level Set Method"

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Schnurr, Jonas, Momme Adami, and Mirko Skiborowski. "Refrigerant Selection and Cycle Design for Industrial Heat Pump Applications exemplified for Distillation Processes." In The 35th European Symposium on Computer Aided Process Engineering. PSE Press, 2025. https://doi.org/10.69997/sct.119494.

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Mechanical compression heat pumps are indispensable to facilitate the transition from thermally driven processes to renewable energy by electrification, upgrading low-temperature waste heat to recycle it at a higher temperature level. However, the implementation of such heat pumps up to date encounters limitations, due to equipment limitations and a lack of tools for the design of process concepts for the application of high-temperature heat pumps. The optimal design of heat pumps relies heavily on the selection of an appropriate refrigerant, as the thermodynamic properties significantly affect the heat pump cycle design and performance. While existing methods are capable of identifying thermodynamically beneficial refrigerants, they do not directly account for practical constraints such as limitations on the compressor discharge temperature, compression ratio, and vacuum operation. The current study proposes a fast-screening approach for arbitrary heat pump applications, considering a large set of established refrigerants. The method automatically assesses the performance of the refrigerants for a specified set of heat sink and source, adjusting the heat pump design with an optional internal heat exchanger in case of necessary superheating prior to compression. The approach is illustrated for the evaluation of heat pump-assisted distillation processes.

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Li Xiao-Lin, Guan Ming-You, and Wang Xiu-Li. "Fast level set method with dichromatic reflection model." In 2009 International Conference on Image Analysis and Signal Processing. IEEE, 2009. http://dx.doi.org/10.1109/iasp.2009.5054657.

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Alashwal, Nagi H., and Farhan M. A. Nashwan. "A fast level set method for object tracking." In 2014 International Conference on Engineering and Technology (ICET). IEEE, 2014. http://dx.doi.org/10.1109/icengtechnol.2014.7016760.

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Dizdaroglu, Bekir. "Retinal vasculature segmentation based on fast level set method." In 2015 23th Signal Processing and Communications Applications Conference (SIU). IEEE, 2015. http://dx.doi.org/10.1109/siu.2015.7129963.

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Gaofei Ouyang and Xianmin Zhang. "Research on Fast Initialization for the Level Set Method." In 2006 6th World Congress on Intelligent Control and Automation. IEEE, 2006. http://dx.doi.org/10.1109/wcica.2006.1713939.

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Kashyap, Ramgopal, and Pratima Gautam. "Fast Level Set Method for Segmentation of Medical Images." In ICIA-16: International Conference on Informatics and Analytics. ACM, 2016. http://dx.doi.org/10.1145/2980258.2980302.

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Bernard, O., D. Friboulet, P. Thevenaz, and M. Unser. "Variational B-spline level-set method for fast image segmentation." In 2008 5th IEEE International Symposium on Biomedical Imaging (ISBI 2008). IEEE, 2008. http://dx.doi.org/10.1109/isbi.2008.4540961.

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Zhang, Li-jun, Xiao-juan Wu, and Zan Sheng. "A Fast Image Segmentation Approach based on Level Set Method." In 2006 8th international Conference on Signal Processing. IEEE, 2006. http://dx.doi.org/10.1109/icosp.2006.345707.

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Gambini, Juliana, Damian Rozichner, María E. Buemi, Marta Mejail, and Julio Jacobo Berllés. "Occlusion Handling for Object Tracking Using a Fast Level Set Method." In 2008 XXI Brazilian Symposium on Computer Graphics and Image Processing (SIBGRAPI). IEEE, 2008. http://dx.doi.org/10.1109/sibgrapi.2008.36.

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Zhang, Jun, Ning Li, and Y. F. Li. "The detection of multiple moving objects using fast level set method." In 2008 IEEE International Joint Conference on Neural Networks (IJCNN 2008 - Hong Kong). IEEE, 2008. http://dx.doi.org/10.1109/ijcnn.2008.4633986.

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Reports on the topic "And Fast Level Set Method"

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Isakov, Victor, Shingyu Leung, and Jianliang Qian. A Fast Local Level Set Method for Inverse Gravimetry. Cogeo@oeaw-giscience, 2011. http://dx.doi.org/10.5242/iamg.2011.0066.

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2

Enright, Douglas, Frank Losasso, and Ronald Fedkiw. A Fast and Accurate Semi-Lagrangian Particle Level Set Method. Defense Technical Information Center, 2004. http://dx.doi.org/10.21236/ada479118.

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3

Cecil, T. C., S. J. Osher, and J. Qian. Simplex Free Adaptive Tree Fast Sweeping and Evolution Methods for Solving Level Set Equations in Arbitrary Dimension. Defense Technical Information Center, 2005. http://dx.doi.org/10.21236/ada438295.

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4

Tan, Peng, and Nicholas Sitar. Parallel Level-Set DEM (LS-DEM) Development and Application to the Study of Deformation and Flow of Granular Media. Pacific Earthquake Engineering Research Center, University of California, Berkeley, CA, 2023. http://dx.doi.org/10.55461/kmiz5819.

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Abstract:

We present a systematic investigation of computational approaches to the modeling of granular materials. Granular materials are ubiquitous in everyday life and in a variety of engineering and industrial applications. Despite the apparent simplicity of the laws governing particle-scale interactions, predicting the continuum mechanical response of granular materials still poses extraordinary challenges. This is largely due to the complex history dependence resulting from continuous rearrangement of the microstructure of granular material, as well as the mechanical interlocking due to grain morphology and surface roughness. X-Ray Computed Tomography (XRCT) is used to characterize the grain morphology and the fabric of the granular media, naturally deposited sand in this study. The Level-Set based Discrete Element Method (LS-DEM) is then used to bridge the granular behavior gap between the micro and macro scale. The LS-DEM establishes a one-to-one correspondence between granular objects and numerical avatars and captures the details of grain morphology and surface roughness. However, the high-fidelity representation significantly increases the demands on computational resources. To this end a parallel version of LS-DEM is introduced to significantly decrease the computational demands. The code employs a binning algorithm, which reduces the search complexity of contact detection from O(n2) to O(n), and a domain decomposition strategy is used to elicit parallel computing in a memory- and communication-efficient manner. The parallel implementation shows good scalability and efficiency. High fidelity LS avatars obtained from XRCT images of naturally deposited sand are then used to replicate the results of triaxial tests using the new, parallel LS-DEM code. The result show that both micro- and macro-mechanical behavior of natural material is well captured and is consistent with experimental data, confirming experimental observation that the primary source of peak strength of sand is the mechanical interlocking between irregularly shaped grains. Specifically, triaxial test simulations with a flexible membrane produce a very good match to experimentally observed relationships between deviatoric stress and mobilized friction angle for naturally deposited sand. We then explore the viability of modeling dynamic problems with a new formulation of an impulse based LS-DEM. The new formulation is stable, fast, and energy conservative. However, it can be numerically stiff when the assembly has substantial mass differences between particles. We also demonstrate the feasibility of modeling deformable structures in the rigid body framework and propose several enhancements to improve the convergence of collision resolution, including a hybrid time integration scheme to separately handle at rest contacts and dynamic collisions. Finally, we extend the impulse-based LS-DEM to include arbitrarily shaped topographic surfaces and exploit its algorithmic advantages to demonstrate the feasibility of modeling realistic behavior of granular flows. The novel formulation significantly improves performance of dynamic simulations by allowing larger time steps, which is advantageous for observing the full development of physical phenomena such as rock avalanches, which we present as an illustrative example.

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Milne, Roger Brent. An adaptive level set method. Office of Scientific and Technical Information (OSTI), 1995. http://dx.doi.org/10.2172/395612.

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6

Rehm, Ronald G. Fire-front propagation using the level set method. National Bureau of Standards, 2009. http://dx.doi.org/10.6028/nist.tn.1611.

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Lei, Hongzhuan, Zhiming Lu, and Velimir Valentinov Vesselinov. Identifying Heterogeneities in Subsurface Environment using the Level Set Method. Office of Scientific and Technical Information (OSTI), 2016. http://dx.doi.org/10.2172/1312562.

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Estellers, Virginia, Dominique Zosso, Rongjie Lai, Jean-Philippe Thiran, Stanley Osher, and Xavier Bresson. An Efficient Algorithm for Level Set Method Preserving Distance Function. Defense Technical Information Center, 2011. http://dx.doi.org/10.21236/ada557314.

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9

Carrica, P. M., R. V. Wilson, and F. Stern. An Unsteady Single-Phase Level Set Method for Viscous Free Surface Flows. Defense Technical Information Center, 2005. http://dx.doi.org/10.21236/ada450120.

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Garzon, M., D. Adalsteinsson, L. Gray, and J. A. Sethian. Wave breaking over sloping beaches using a coupled boundary integral-level set method. Office of Scientific and Technical Information (OSTI), 2003. http://dx.doi.org/10.2172/840733.

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