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Author |
Oriol Pujol; Petia Radeva |
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Title |
Texture Segmentation by Statistical Deformable Models |
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2004 |
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International Journal of Image and Graphics |
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IJIG |
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4 |
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3 |
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433-452 |
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Texture segmentation, parametric active contours, statistic snakes |
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Deformable models have received much popularity due to their ability to include high-level knowledge on the application domain into low-level image processing. Still, most proposed active contour models do not sufficiently profit from the application information and they are too generalized, leading to non-optimal final results of segmentation, tracking or 3D reconstruction processes. In this paper we propose a new deformable model defined in a statistical framework to segment objects of natural scenes. We perform a supervised learning of local appearance of the textured objects and construct a feature space using a set of co-occurrence matrix measures. Linear Discriminant Analysis allows us to obtain an optimal reduced feature space where a mixture model is applied to construct a likelihood map. Instead of using a heuristic potential field, our active model is deformed on a regularized version of the likelihood map in order to segment objects characterized by the same texture pattern. Different tests on synthetic images, natural scene and medical images show the advantages of our statistic deformable model. |
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MILAB;HuPBA |
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BCNPCL @ bcnpcl @ PuR2004a |
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505 |
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Author |
Josep Llados; Gemma Sanchez |
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Title |
Graph Matching vs. Graph Parsing in Graphics Recognition: A Combined Approach |
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2004 |
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International Journal of Pattern Recognition and Artificial Intelligence |
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IJPRAI |
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18 |
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3 |
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455–473 |
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DAG; IF: 0.588 |
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DAG @ dag @ LlS2004 |
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445 |
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Petia Radeva; Jordi Vitria |
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Corkinspect: Statistical Learning of Natural Material |
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2004 |
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Italian Beverage Technology, 13(38):11–18 |
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OR;MILAB;MV |
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BCNPCL @ bcnpcl @ RaV2004b |
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514 |
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Debora Gil; Petia Radeva |
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Title |
Shape Restoration via a Regularized Curvature Flow |
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2004 |
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Journal of Mathematical Imaging and Vision |
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21 |
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3 |
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205-223 |
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Any image filtering operator designed for automatic shape restoration should satisfy robustness (whatever the nature and degree of noise is) as well as non-trivial smooth asymptotic behavior. Moreover, a stopping criterion should be determined by characteristics of the evolved image rather than dependent on the number of iterations. Among the several PDE based techniques, curvature flows appear to be highly reliable for strongly noisy images compared to image diffusion processes.
In the present paper, we introduce a regularized curvature flow (RCF) that admits non-trivial steady states. It is based on a measure of the local curve smoothness that takes into account regularity of the curve curvature and serves as stopping term in the mean curvature flow. We prove that this measure decreases over the orbits of RCF, which endows the method with a natural stop criterion in terms of the magnitude of this measure. Further, in its discrete version it produces steady states consisting of piece-wise regular curves. Numerical experiments made on synthetic shapes corrupted with different kinds of noise show the abilities and limitations of each of the current geometric flows and the benefits of RCF. Finally, we present results on real images that illustrate the usefulness of the present approach in practical applications. |
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IAM @ iam @ GiR2004c |
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1532 |
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Author |
Josep Llados; Young-Bin Kwon |
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Title |
Graphics Recognition. Recent Advances and Perspectives |
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2004 |
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LNCS 3080, ISBN: 3–540–22478–5 |
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DAG @ dag @ LlK2004 |
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515 |
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Misael Rosales; Petia Radeva; J. Mauri; Oriol Pujol |
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Title |
Simulation Model of Intravascular Ultrasound Images |
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2004 |
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MICCAI, 2004, Saint Melo, France |
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Springer Verlag |
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MILAB;HuPBA |
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BCNPCL @ bcnpcl @ RRM2004b |
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464 |
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Author |
Xavier Otazu; M. Ribo; J.M. Paredes; M. Peracaula; J. Nuñez |
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Title |
Multiresolution approach for period determination on unevenly sampled data |
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2004 |
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Monthly Notices of the Royal Astronomical Society, 351:251–219 (IF: 5.238) |
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CIC |
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CAT @ cat @ ORP2004 |
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451 |
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Author |
Jian Yang; Zhong Jin; Jing-Yu Yang; David Zhang; Alejandro F. Frangi |
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Title |
Essence of kernel Fisher discriminant: KPCA plus LDA |
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2004 |
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Pattern Recognition, 37(10): 2097–2100 (IF: 2.176) |
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Admin @ si @ YJY2004 |
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480 |
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Author |
Yong Xu; Jing-Yu Yang; Zhong Jin |
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A novel method for Fisher discriminant analysis |
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2004 |
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Pattern Recognition, 37(2):381–384 (IF: 2.176) |
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Author |
Jordi Gonzalez |
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Title |
Human Sequence Evaluation: the Key-frame Approach |
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2004 |
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PhD Thesis, Universitat Autonoma de Barcelona-CVC |
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Xavier Roca;Javier Varona |
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ISE @ ise @ Gon2004 |
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362 |
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David Guillamet |
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Title |
Statistical Local Appearance Models for Object Recognition |
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2004 |
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PhD Thesis, Universitat Autonoma de Barcelona-CVC |
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Bellaterra |
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Ph.D. thesis |
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Jordi Vitria |
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Admin @ si @ Gui2004 |
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444 |
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Oriol Pujol |
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A semi-Supervised Statistical Framework and Generative Snakes for IVUS Analysis |
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2004 |
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PhD Thesis, Universitat Autonoma de Barcelona-CVC |
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CVC (UAB), Bellaterra |
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Ph.D. thesis |
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Petia Radeva |
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HuPBA;MILAB |
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BCNPCL @ bcnpcl @ Puj2004 |
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512 |
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Author |
Debora Gil |
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Title |
Geometric Differential Operators for Shape Modelling |
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2004 |
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PhD Thesis, Universitat Autonoma de Barcelona-CVC |
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Medical imaging feeds research in many computer vision and image processing fields: image filtering, segmentation, shape recovery, registration, retrieval and pattern matching. Because of their low contrast changes and large variety of artifacts and noise, medical imaging processing techniques relying on an analysis of the geometry of image level sets rather than on intensity values result in more robust treatment. From the starting point of treatment of intravascular images, this PhD thesis ad- dresses the design of differential image operators based on geometric principles for a robust shape modelling and restoration. Among all fields applying shape recovery, we approach filtering and segmentation of image objects. For a successful use in real images, the segmentation process should go through three stages: noise removing, shape modelling and shape recovery. This PhD addresses all three topics, but for the sake of algorithms as automated as possible, techniques for image processing will be designed to satisfy three main principles: a) convergence of the iterative schemes to non-trivial states avoiding image degeneration to a constant image and representing smooth models of the originals; b) smooth asymptotic behav- ior ensuring stabilization of the iterative process; c) fixed parameter values ensuring equal (domain free) performance of the algorithms whatever initial images/shapes. Our geometric approach to the generic equations that model the different processes approached enables defining techniques satisfying all the former requirements. First, we introduce a new curvature-based geometric flow for image filtering achieving a good compromise between noise removing and resemblance to original images. Sec- ond, we describe a new family of diffusion operators that restrict their scope to image level curves and serve to restore smooth closed models from unconnected sets of points. Finally, we design a regularization of snake (distance) maps that ensures its smooth convergence towards any closed shape. Experiments show that performance of the techniques proposed overpasses that of state-of-the-art algorithms. |
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Ph.D. thesis |
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Ediciones Graficas Rey |
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Barcelona (Spain) |
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Jordi Saludes i Closa;Petia Radeva |
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IAM @ iam @ GIL2004 |
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1517 |
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Aura Hernandez-Sabate; Debora Gil; Petia Radeva; E.N.Nofrerias |
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Anisotropic processing of image structures for adventitia detection in intravascular ultrasound images |
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2004 |
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Proc. Computers in Cardiology |
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31 |
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229-232 |
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The adventitia layer appears as a weak edge in IVUS images with a non-uniform grey level, which difficulties its detection. In order to enhance edges, we apply an anisotropic filter that homogenizes the grey level along the image significant structures (ridges, valleys and edges). A standard edge detector applied to the filtered image yields a set of candidate points prone to be unconnected. The final model is obtained by interpolating the former line segments along the tangent direction to the level curves of the filtered image with an anisotropic contour closing technique based on functional extension principles |
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IAM @ iam @ HGR2004 |
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1555 |
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Oriol Pujol; Petia Radeva; Jordi Vitria; J. Mauri |
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Title |
Adaboost to Classify Plaque Appearance in IVUS Images |
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Miscellaneous |
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2004 |
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Progress in Pattern Recognition, Image Analysis and Applications, LNCS 3287:629–636 |
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Puebla (Mexico) |
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BCNPCL @ bcnpcl @ PRV2004 |
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472 |
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