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Digital topology of sets of convex voxels

Graphical Models 2000年第5期62卷 343-352页

作者： Saha, Punam K. Rosenfeld, Azriel Medical Image Processing Group University of Pennsylvania Philadelphia PA 19104-6021 United States Computer Vision Laboratory Center for Automation Research University of Maryland College Park MA 20742-3275 United States

Classical digital geometry deals with sets of cubical voxels (or square pixels) that can share faces, edges, or vertices, but basic parts of digital geometry can be generalized to sets S of convex voxels (or pixels) that can have arbitrary intersections. In particular, it can be shown that if each voxel P of S has only finitely many neighbors (voxels of S that intersect P), and if any nonempty intersection of neighbors of P intersects P, then the neighborhood N(P) of every voxel P is simply connected and without cavities, and if the topology of N(P) does not change when P is deleted (i.e., P is a 'simple' voxel), then deletion of P does not change the topology of S.

关键词： Topology

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Coral reef mosaicking using Teardrop and Fast image Labeling

Coral reef mosaicking using Teardrop and Fast Image Labeling

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OCEANS - Europe

作者： Francis James Corpuz Prospero Naval Eusebio Capili Jaylord Jauod Roel John Judilla Maricor Soriano Vision and Image Processing Group Instrumentation Physics Laboratory National Institute of Physics Computer Vision and Machine Intelligence Group Department of Computer Science College of Engineering University of Philippines Quezon Philippines Computer Vision and Machine Intelligence Group Department of Computer Science College of Engineering University of Philippines Quezon Philippines Mapua Robotics Center Special Projects Laboratory Institutional Laboratory Mgmt Office Mapua Institute of Technology Manila Philippines Vision and Image Processing Group Instrumentation Physics Laboratory National Institute of Physics University of Philippines Quezon Philippines

In this paper, we present an inexpensive system for diverless video capture and fast image stitching of image frames for rapid reef assessment of shallow coral reefs. Our system has two main components: 1) Teardrop, a boat-towable, winged hull apparatus designed to house a commercial digital camera, and 2) a mosaicking algorithm to stitch the coral reef video into mosaics for further appreciation and analysis. The captured reef video is then separated into image frames which are to be stitched sequentially using Fast image Labeling. The overlap between image frames is estimated using Single-Step DFT, an efficient sub-pixel estimation algorithm. The estimated overlap is used to compute for the area to be added to the mosaic space. The overlapping section between succeeding image-pairs are stitched along a seam determined by a minimal-cost path using dynamic programming. The visibility of the seam boundaries is further minimized by utilizing blending on multi-resolution splines. Experimental results on automated reef mosaics creation from actual coral reef video taken using Teardrop shows the performance of the system described. The main contribution of this work is the demonstration of a rapid reef visualization system using a diverless system and commercially available, non-research-grade imaging equipment.

关键词： image segmentation Sea measurements Cameras Labeling Discrete Fourier transforms Sea floor

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Motion constraint patterns

Motion constraint patterns

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IEEE Workshop on Qualitative vision

作者： C. Fermuller Department for Pattern Recognition and Image Processing Institute for Automation Technical University of of Vienna Vienna Austria Computer Vision Laboratory Center for Automation Research University of Maryland College Park MD USA

The problem of egomotion recovery has been treated by using as input local image motion, with the published algorithms utilizing the geometric constraint relating 2-D local image motion (optical flow, correspondence, derivatives of the image flow) to 3-D motion and structure. Since it has proved very difficult to achieve accurate input (local image motion), a lot of effort has been devoted to the development of robust techniques. A new approach to the problem of egomotion estimation is taken, based on constraints of a global nature. It is proved that local normal flow measurements form global patterns in the image plane. The position of these patterns is related to the three dimensional motion parameters. By locating some of these patterns, which depend only on subsets of the motion parameters, through a simple search technique, the 3-D motion parameters can be found. The proposed algorithmic procedure is very robust, since it is not affected by small perturbations in the normal flow measurements. As a matter of fact, since only the sign of the normal flow measurement is employed, the direction of translation and the axis of rotation can be estimated with up to 100% error in the image measurements.< >

关键词： Motion estimation computer vision Automation image motion analysis Fluid flow measurement Motion measurement Rotation measurement Laboratories Educational institutions Geometrical optics

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Building and registering parameterized 3D models of vessel trees for visualization during intervention

Building and registering parameterized 3D models of vessel t...

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International Conference on Pattern Recognition

作者： G. Langs P. Radeva D. Rotger F. Carreras Insitute for Computer Graphics and Vision Graz University of Technology Graz Austria Pattern Recognition and Image Processing Group Vienna University of Technology Vienna Austria Computer Vision Center Universitat Autònoma de Barcelona Bellaterra Spain Hospital St. Pau Barcelona Spain

In this paper, we address the problem of multimodal registration of coronary vessels by developing a 3D parametrical model of vessel trees from computer tomography data and registering it to angiography images during intervention. Thus, the interventionist takes profit from 3D data otherwise only available before the intervention. This facilitates orientation in ambiguous radiographs, interactive visualization of all vessel structures to estimate their mutual position and navigation within the vessel system and ultimately reduces the radiation the patient and the physicians are exposed to. The model is build by exploring the branching vessel tree starting from a single position and successively expanding through the vessels guided by a local deformable surface. The result is a tree of cylindrical segments each adapted to the vessel walls that is registered to angiography images in a fast and robust way. Validation on 8 patients confirms the robustness of our method.

关键词： X-ray imaging Computed tomography Robustness Angiography image segmentation image reconstruction Distortion measurement Tree graphs Data visualization Radio navigation

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Blessemflood21: Advancing Flood Analysis with a High-Resolution Georeferenced Dataset for Humanitarian Aid Support

Blessemflood21: Advancing Flood Analysis with a High-Resolut...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Vladyslav Polushko Alexander Jenal Jens Bongartz Immanuel Weber Damjan Hatic Ronald Rösch Thomas März Markus Rauhut Andreas Weinmann Image Processing Department Fraunhofer ITWM Kaiserslautern Germany Working Group Algorithms for Computer Vision Imaging and Data Analysis Darmstadt Germany Center for Machine Learning and Sensor Technology Hochschule Koblenz Remagen Germany

ISBN: (数字)9798350360325

ISBN: (纸本)9798350360332

Floods are an increasingly common global threat, causing emergencies and severe damage to infrastructure. During crises, organisations such as the World Food Programme use remotely sensed imagery, typically obtained through drones, for rapid situational analysis to plan life-saving actions. computer vision tools are needed to support task force experts on-site in the evaluation of the imagery to improve their efficiency and to allocate resources strategically. We introduce the BlessemFlood21 dataset to stimulate research on efficient flood detection tools. The imagery was acquired during the 2021 Erftstadt-Blessem flooding event and consists of high-resolution and georeferenced RGB-NIR images. In the resulting RGB dataset, the images are supplemented with detailed water masks, obtained via a semi-supervised human-in-the-loop technique, where in particular the NIR information is leveraged to classify pixels as either water or non-water. We evaluate our dataset by training and testing established Deep Learning models for semantic segmentation. With BlessemFlood21 we provide labeled high-resolution RGB data and a baseline for further development of algorithmic solutions tailored to flood detection in RGB imagery.

关键词： Deep learning Training Semantic segmentation Human in the loop Sensors Floods Task analysis

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Small-size lung nodule modeling and detection with clinical evaluation

Small-size lung nodule modeling and detection with clinical ...

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Cairo International Biomedical Engineering Conference, CIBEC

作者： Amal Farag James Graham Hossam Abdelmunim Salwa Elshazly Mohamed Ei-Mogy Sabry Ei-Mogy Robert Falk Aly A. Farag Computer Vision and Image Processing Laboratory (CVIP Lab) University of Louisville Louisville KY Computer & Systems Engineering Department Ain Shams University Cairo Mogy-Scan Center Mansoura Egypt Jewish Hospital and 3DR Louisville Kentucky

In this paper examination of the template modeling process using the Active Appearance Modeling (AAM) approach for automatic detection of lung nodules is investigated. A template matching approach is formulated to compute a similarity score between the AAM templates and the input lung CT slice, where the goal is to maximize the similarity measure at different image pixels to increase nodule detection. The template matching approach is implemented using nine similarity measures. Performance validation for the robustness of the generated models is tested on three clinical databases.

关键词： Lungs Databases Computed tomography Principal component analysis Computational modeling Solid modeling

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A layered approach to robust lane detection at night

A layered approach to robust lane detection at night

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IEEE Workshop on Computational Intelligence in Vehicles and Vehicular Systems, CIVVS

作者： Amol Borkar Monson Hayes Mark T. Smith Sharathchandra Pankanti Center of Signal and Image Processing (CSIP) Georgia Institute of Technology USA Department of Communication Systems KTH Swedish Royal Institute of Technology Sweden Exploratory Computer Vision Group (ECVG) IBM Thomas J. Watson Research Center USA

A layered approach is designed to address many of the real-world problems that an inexpensive lane detection system would encounter. A region of interest is first extracted from the image followed by an enhancement procedure to manipulate the shape of the lane markers. The extracted region is then converted to binary using an adaptive threshold. A model based line detection system hypothesizes lane position. Finally, an iterated matched filtering scheme estimates the final lane position. The developed system shows good performance when tested on real-world data that contains fluctuating illumination and a variety of traffic conditions.

关键词： Robustness image edge detection Cameras image converters Lighting Road accidents Automobiles Pixel Road transportation image segmentation

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BLESSEMFLOOD21: ADVANCING FLOOD ANALYSIS WITH A HIGH-RESOLUTION GEOREFERENCED DATASET FOR HUMANITARIAN AID SUPPORT

arXiv

引用

arXiv 2024年

作者： Polushko, Vladyslav Jenal, Alexander Bongartz, Jens Weber, Immanuel Hatic, Damjan Rösch, Ronald März, Thomas Rauhut, Markus Weinmann, Andreas Image Processing Department Fraunhofer ITWM Kaiserslautern Germany Working Group Algorithms for Computer Vision Imaging and Data Analysis Hochschule Darmstadt Darmstadt Germany Center for Machine Learning and Sensor Technology Hochschule Koblenz Remagen Germany

关键词： Floods

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An AAM-based detection approach of lung nodules from LDCT scans

An AAM-based detection approach of lung nodules from LDCT sc...

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IEEE International Symposium on Biomedical Imaging

作者： Amal Farag Hossam Abdelmunim James Graham Aly A. Farag Cambron Carter Salwa Elshazly Mohamed S. El-Mogy Sabry El-Mogy Robert Falk Computer Vision and Image Processing Laboratory (CVIP Lab) University of Louisville Louisville KY 40292 University of Louisville Louisville KY US Mogy Scan Center Mansoura Egypt Jewish Hospital and 3DR Louisville Kentucky

ISBN: (纸本)9781457718571

In this, paper a new approach for lung nodules detection from LDCT scans is proposed. Intensity models of the nodules are generated using an active appearance model formulation. Template matching is used to compute a similarity score between the AAM template and the input image. The goal is to maximize the similarity measure at different image pixels to increase nodule detection. Conventional template matching does not account for rotation variations. Our proposed template matching approach is formulated as an energy optimization problem that computes a transformation that includes rotation(s) parameters as well as the AAM weighting coefficients. The approach is flexible to different scans and different nodule locations because of the ability to handle the variations in the rotation between the template and the input images. The approach can employ different similarity measures. Experimental results will be shown using three similarity measures from the literature: NCC, ZNCC and ZSSD; which illustrate the efficiency of the proposed approach. ROC curves for various nodule types are constructed on a clinical study with known ground truth, showing significant enhancements over conventional parametric nodule models and traditional template matching criterion.

关键词： Lungs Computational modeling Active appearance model Solid modeling Correlation Computed tomography Shape

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A Non-Linear Diffeomorphic Framework for Prostate Multimodal Registration

A Non-Linear Diffeomorphic Framework for Prostate Multimodal...

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Proceedings of the Digital image Computing: Technqiues and Applications (DICTA)

作者： Jhimli Mitra Zoltan Kato Robert Marti Arnau Oliver Xavier Llado Soumya Ghose Joan C. Vilanova Fabrice Meriaudeau Computer Vision and Robotics Group Universitat de Girona Girona Spain Le2i-UMR CNRS 5158 Université de Bourgogne Le Creusot France Department of Image Processing and Computer Graphics University of Szeged Szeged Hungary Girona Magnetic Resonance Center Girona Spain

This paper presents a novel method for non-rigid registration of prostate multimodal images based on a nonlinear framework. The parametric estimation of the non-linear diffeomorphism between the 2D fixed and moving images has its basis in solving a set of non-linear equations of thin-plate splines. The regularized bending energy of the thin-plate splines along with the localization error of established correspondences is jointly minimized with the fixed and transformed image difference, where, the transformed image is represented by the set of non-linear equations defined over the moving image. The traditional thin-plate splines with established correspondences may provide good registration of the anatomical targets inside the prostate but may fail to provide improved contour registration. On the contrary, the proposed framework maintains the accuracy of registration in terms of overlap due to the non-linear thin-plate spline functions while also producing smooth deformations of the anatomical structures inside the prostate as a result of established corrspondences. The registration accuracies of the proposed method are evaluated in 20 pairs of prostate mid-gland ultrasound and magnetic resonance images in terms of Dice similarity coefficient with an average of 0.982 ± 0.004, average 95% Hausdorff distance of 1.54 ± 0.46 mm and mean target registration and target localization errors of 1.90±1.27 mm and 0.15 ± 0.12 mm respectively.

关键词： Biopsy Magnetic resonance imaging Equations Spline Glands High definition video Accuracy

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