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147
From Template to Image: Reconstructing Fingerprints from Minutiae Points
 IEEE Transactions of Pattern Analysis and Machine Translation
, 2007
"... Abstract—Most fingerprintbased biometric systems store the minutiae template of a user in the database. It has been traditionally assumed that the minutiae template of a user does not reveal any information about the original fingerprint. In this paper, we challenge this notion and show that three ..."
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Cited by 46 (9 self)
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Abstract—Most fingerprintbased biometric systems store the minutiae template of a user in the database. It has been traditionally assumed that the minutiae template of a user does not reveal any information about the original fingerprint. In this paper, we challenge this notion and show that three levels of information about the parent fingerprint can be elicited from the minutiae template alone, viz., 1) the orientation field information, 2) the class or type information, and 3) the friction ridge structure. The orientation estimation algorithm determines the direction of local ridges using the evidence of minutiae triplets. The estimated orientation field, along with the given minutiae distribution, is then used to predict the class of the fingerprint. Finally, the ridge structure of the parent fingerprint is generated using streamlines that are based on the estimated orientation field. Line Integral Convolution is used to impart texture to the ensuing ridges, resulting in a ridge map resembling the parent fingerprint. The salient feature of this noniterative method to generate ridges is its ability to preserve the minutiae at specified locations in the reconstructed ridge map. Experiments using a commercial fingerprint matcher suggest that the reconstructed ridge structure bears close resemblance to the parent fingerprint.
A LevelSet Method for Flow Visualization
 IN PROCEEDINGS OF VIZ2000, IEEE VISUALIZATION
, 2000
"... In this paper we propose a technique for visualizing steady flow. Using this technique, we first convert the vector field data into a scalar levelset representation. We then analyze the dynamic behavior and subsequent distortion of levelsets and interactively monitor the evolving structures by mea ..."
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Cited by 44 (1 self)
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In this paper we propose a technique for visualizing steady flow. Using this technique, we first convert the vector field data into a scalar levelset representation. We then analyze the dynamic behavior and subsequent distortion of levelsets and interactively monitor the evolving structures by means of texturebased surface rendering. Next, we combine geometrical and topological considerations to derive a multiscale representation and to implement a method for the automatic placement of a sparse set of graphical primitives depicting homogeneous streams in the fields. Using the resulting algorithms, we have built a visualization system that enables us to effectively display the flow direction and its dynamics even for dense 3D fields.
Investigating Swirl and Tumble Flow with a Comparison of Visualization Techniques
 IN PROCEEDINGS IEEE VISUALIZATION ’04
, 2004
"... We investigate two important, common fluid flow patterns from computational fluid dynamics (CFD) simulations, namely, swirl and tumble motion typical of automotive engines. We study and visualize swirl and tumble flow using three different flow visualization techniques: direct, geometric, and textur ..."
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Cited by 44 (26 self)
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We investigate two important, common fluid flow patterns from computational fluid dynamics (CFD) simulations, namely, swirl and tumble motion typical of automotive engines. We study and visualize swirl and tumble flow using three different flow visualization techniques: direct, geometric, and texturebased. When illustrating these methods sidebyside, we describe the relative strengths and weaknesses of each approach within a specific spatial dimension and across multiple spatial dimensions typical of an engineer 's analysis. Our study is focused on steadystate flow. Based on this investigation we offer perspectives on where and when these techniques are best applied in order to visualize the behavior of swirl and tumble motion.
Stylized Video Cubes
 In ACM SIGGRAPH Symposium on Computer Animation
, 2002
"... We present a new set of nonphotorealistic rendering (NPR) tools for processing video. Our approach is to treat the video as a spacetime volume of image data. Previous tools to process video for an impressionist effect have painted collections of twodimensional strokes on each successive frame of v ..."
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Cited by 43 (2 self)
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We present a new set of nonphotorealistic rendering (NPR) tools for processing video. Our approach is to treat the video as a spacetime volume of image data. Previous tools to process video for an impressionist effect have painted collections of twodimensional strokes on each successive frame of video. In contrast, we create a set of “rendering solids. ” Each rendering solid is a function defined over an interval of time; when evaluated at a particular time within that interval, it provides parameters necessary for rendering an NPR primitive. Rendering solids can be rendered interactively, giving immediate feedback to an artist along with the ability to modify styles in real time. Benefits of our approach include: a more unified treatment of the video volume’s spatial and temporal dimensions; interactive, aesthetic flexibility and control; and the extension of stylized rendering techniques for video beyond the impressionist styles previously explored. We show example styles inspired by impressionist, cubist, and abstract art of the past century. Figure 1: Example NPR video styles created with our system. 1
Strategies for Interactive Exploration of 3D Flow Using EvenlySpaced Illuminated Streamlines
, 2003
"... This paper presents several strategies to interactively explore 3D flow. Based on a fast illuminated streamlines algorithm, standard graphics hardware is sufficient to gain interactive rendering rates. Our approach does not require the user to have any prior knowledge of flow features. After the str ..."
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Cited by 31 (2 self)
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This paper presents several strategies to interactively explore 3D flow. Based on a fast illuminated streamlines algorithm, standard graphics hardware is sufficient to gain interactive rendering rates. Our approach does not require the user to have any prior knowledge of flow features. After the streamlines are computed in a short preprocessing time, the user can interactively change appearance and density of the streamlines to further explore the flow. Most important flow features like velocity or pressure not only can be mapped to all available streamline appearance properties like streamline width, material, opacity, but also to streamline density. To improve spatial perception of the 3D flow we apply techniques based on animation, depth cueing, and halos along a streamline if it is crossed by another streamline in the foreground. Finally, we make intense use of focus+context methods like magic volumes, region of interest driven streamline placing, and spotlights to solve the occlusion problem.
Flow Field Clustering via Algebraic Multigrid
 In Proc. IEEE Visualization Conf. ’04
, 2004
"... We present a novel multiscale approach for flow visualization. We define a local alignment tensor that encodes a measure for alignment to the direction of a given flow field. This tensor induces an anisotropic differential operator on the flow domain, which is discretized with a standard finite elem ..."
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Cited by 30 (4 self)
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We present a novel multiscale approach for flow visualization. We define a local alignment tensor that encodes a measure for alignment to the direction of a given flow field. This tensor induces an anisotropic differential operator on the flow domain, which is discretized with a standard finite element technique. The entries of the corresponding stiffness matrix represent the anisotropically weighted couplings of adjacent nodes of the domain mesh. We use an algebraic multigrid algorithm to generate a hierarchy of fine to coarse descriptions for the above coupling data. This hierarchy comprises a set of coarse grid nodes, a multiscale of basis functions and their corresponding supports. We use these supports to obtain a multilevel decomposition of the flow structure. Standard streamline icons are used to visualize this decomposition at any userselected level of detail. The method provides a single framework for vector field decomposition independent on the domain dimension or mesh type. Applications are shown in 2D, for flow fields on curved surfaces, and for 3D volumetric flow fields. 1
The motion map: Efficient computation of steady flow animations
 Proceedings of the 8th Annual IEEE Conference on Visualization (VISU97), pages 323–328, Los Alamitos, October19–24
, 1997
"... This paper presents a new approach for animating 2D steady flow fields. It is based on an original data structure called the Motion Map. The Motion Map contains not only a dense representation of the flow field but also all the motion information required to animate the flow. An important feature of ..."
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Cited by 28 (1 self)
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This paper presents a new approach for animating 2D steady flow fields. It is based on an original data structure called the Motion Map. The Motion Map contains not only a dense representation of the flow field but also all the motion information required to animate the flow. An important feature of this method is that it allows, in a natural way, cyclical variablespeed animations. As far as efficiency is concerned, the advantage of this method is that computing the Motion Map does not take more time than computing a single still image of the flow and the Motion Map has to be computed only once. Another advantage is that the memory requirements for a cyclical animation of an arbitrary number of frames amounts to the memory cost of a single still image. 1
Overview of flow visualization
 The Visualization Handbook
, 2005
"... With increasing computing power, it is possible to process more complex fluid simulations. However, a gap between increasing data size and our ability to visualize them still remains. Despite the great amount of progress that has been made in the field of flow visualization over the last two decades ..."
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Cited by 28 (13 self)
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With increasing computing power, it is possible to process more complex fluid simulations. However, a gap between increasing data size and our ability to visualize them still remains. Despite the great amount of progress that has been made in the field of flow visualization over the last two decades, a number of challenges remain. Whilst the visualization of 2D flow has many good solutions, the visualization of 3D flow still poses many problems. Challenges such as domain coverage, speed of computation, and perception remain key directions for further research. Flow visualization with a focus on surfacebased techniques forms the basis of this literature survey, including surface construction techniques and visualization methods applied to surfaces. We detail our investigation into these algorithms with discussions of their applicability and their relative strengths and drawbacks. We review the most important challenges when considering such visualizations. The result is an uptodate overview of the current stateoftheart that highlights both solved and unsolved problems in this rapidly evolving branch of research.
A Phase Field Model for Continuous Clustering on Vector Fields
 IEEE Transactions on Visualization and Computer Graphics
"... A new method for the simplification of flow fields is presented. It is based on continuous clustering. A wellknown physical clustering model, the Cahn Hilliard model which describes phase separation, is modified to reflect the properties of the data to be visualized. Clusters are defined implicitly ..."
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Cited by 24 (3 self)
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A new method for the simplification of flow fields is presented. It is based on continuous clustering. A wellknown physical clustering model, the Cahn Hilliard model which describes phase separation, is modified to reflect the properties of the data to be visualized. Clusters are defined implicitly as connected components of the positivity set of a density function. An evolution equation for this function is obtained as a suitable gradient flow of an underlying anisotropic energy functional. Here, time serves as the scale parameter. The evolution is characterized by a successive coarsening of patterns — the actual clustering — during which the underlying simulation data specifies preferable pattern boundaries. We introduce specific physical quantities in the simulation to control the shape, orientation and distribution of the clusters, as a function of the underlying flow field. In addition the model is expanded involving elastic effects. Thereby in early stages of the evolution shear layer type representation of the flow field can be generated, whereas for later stages the distribution of clusters can be influenced. Furthermore, we incorporate upwind ideas to give the clusters an oriented drop–shaped appearance. Here we discuss the applicability of this new type of approach mainly for flow fields, where the cluster energy penalizes cross streamline boundaries. However, the method also carries provisions for other fields as well. The clusters can be displayed directly as a flow texture. Alternatively, the clusters can be visualized by iconic representations, which are positioned by using a skeletonization algorithm. 1
H.W.: Illustrative Streamline Placement and Visualization
 In IEEE Pacific Visualization Symposium 2008 (2008), IEEE Computer Society
"... Inspired by the abstracting, focusing and explanatory qualities of diagram drawing in art, in this paper we propose a novel seeding strategy to generate representative and illustrative streamlines in 2D vector fields to enforce visual clarity and evidence. A particular focus of our algorithm is to ..."
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Cited by 20 (0 self)
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Inspired by the abstracting, focusing and explanatory qualities of diagram drawing in art, in this paper we propose a novel seeding strategy to generate representative and illustrative streamlines in 2D vector fields to enforce visual clarity and evidence. A particular focus of our algorithm is to depict the underlying flow patterns effectively and succinctly with a minimum set of streamlines. To achieve this goal, 2D distance fields are generated to encode the distances from each grid point in the field to the nearby streamlines. A local metric is derived to measure the dissimilarity between the vectors from the original field and an approximate field computed from the distance fields. A global metric is used to measure the dissimilarity between streamlines based on the local errors to decide whether to drop a new seed at a local point. This process is iterated to generate streamlines until no more streamlines can be found that are dissimilar to the existing ones. We present examples of images generated from our algorithm and report results from qualitative analysis and user studies. 1