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Author Ernest Valveny; Enric Marti edit   pdf
doi  isbn
openurl 
  Title Hand-drawn symbol recognition in graphic documents using deformable template matching and a Bayesian framework Type Conference Article
  Year 2000 Publication Proc. 15th Int Pattern Recognition Conf Abbreviated Journal  
  Volume 2 Issue Pages 239-242  
  Keywords  
  Abstract Hand-drawn symbols can take many different and distorted shapes from their ideal representation. Then, very flexible methods are needed to be able to handle unconstrained drawings. We propose here to extend our previous work in hand-drawn symbol recognition based on a Bayesian framework and deformable template matching. This approach gets flexibility enough to fit distorted shapes in the drawing while keeping fidelity to the ideal shape of the symbol. In this work, we define the similarity measure between an image and a symbol based on the distance from every pixel in the image to the lines in the symbol. Matching is carried out using an implementation of the EM algorithm. Thus, we can improve recognition rates and computation time with respect to our previous formulation based on a simulated annealing algorithm.  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN 0-7695-0750-6 Medium  
  Area Expedition Conference  
  Notes DAG;IAM; Approved no  
  Call Number IAM @ iam @ VAM2000 Serial 1656  
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Author Josep Llados; Jaime Lopez-Krahe; Enric Marti edit   pdf
doi  openurl
  Title Hand drawn document understanding using the straight line Hough transform and graph matching Type Conference Article
  Year 1996 Publication Proceedings of the 13th International Pattern Recognition Conference (ICPR’96) Abbreviated Journal  
  Volume 2 Issue Pages 497-501  
  Keywords  
  Abstract This paper presents a system to understand hand drawn architectural drawings in a CAD environment. The procedure is to identify in a floor plan the building elements, stored in a library of patterns, and their spatial relationships. The vectorized input document and the patterns to recognize are represented by attributed graphs. To recognize the patterns as such, we apply a structural approach based on subgraph isomorphism techniques. In spite of their value, graph matching techniques do not recognize adequately those building elements characterized by hatching patterns, i.e. walls. Here we focus on the recognition of hatching patterns and develop a straight line Hough transform based method in order to detect the regions filled in with parallel straight fines. This allows not only to recognize filling patterns, but it actually reduces the computational load associated with the subgraph isomorphism computation. The result is that the document can be redrawn by editing all the patterns recognized  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Vienna , Austria Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes DAG;IAM; Approved no  
  Call Number IAM @ iam @ LLM1996 Serial 1579  
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Author Ernest Valveny; Enric Marti edit   pdf
doi  openurl
  Title Learning of structural descriptions of graphic symbols using deformable template matching Type Conference Article
  Year 2001 Publication Proc. Sixth Int Document Analysis and Recognition Conf Abbreviated Journal  
  Volume Issue Pages 455-459  
  Keywords  
  Abstract Accurate symbol recognition in graphic documents needs an accurate representation of the symbols to be recognized. If structural approaches are used for recognition, symbols have to be described in terms of their shape, using structural relationships among extracted features. Unlike statistical pattern recognition, in structural methods, symbols are usually manually defined from expertise knowledge, and not automatically infered from sample images. In this work we explain one approach to learn from examples a representative structural description of a symbol, thus providing better information about shape variability. The description of a symbol is based on a probabilistic model. It consists of a set of lines described by the mean and the variance of line parameters, respectively providing information about the model of the symbol, and its shape variability. The representation of each image in the sample set as a set of lines is achieved using deformable template matching.  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes DAG;IAM; Approved no  
  Call Number IAM @ iam @ VMA2001 Serial 1654  
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Author Josep Llados; Enric Marti; Jaime Lopez-Krahe edit   pdf
doi  openurl
  Title A Hough-based method for hatched pattern detection in maps and diagrams Type Conference Article
  Year 1999 Publication Proceeding of the Fifth Int. Conf. Document Analysis and Recognition ICDAR ’99 Abbreviated Journal  
  Volume Issue Pages 479-482  
  Keywords  
  Abstract A hatched area is characterized by a set of parallel straight lines placed at regular intervals. In this paper, a Hough-based schema is introduced to recognize hatched areas in technical documents from attributed graph structures representing the document once it has been vectorized. Defining a Hough-based transform from a graph instead of the raster image allows to drastically reduce the processing time and, second, to obtain more reliable results because straight lines have already been detected in the vectorization step. A second advantage of the proposed method is that no assumptions must be made a priori about the slope and frequency of hatching patterns, but they are computed in run time for each hatched area.  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes DAG;IAM; Approved no  
  Call Number IAM @ iam @ LIM1999b Serial 1580  
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Author Petia Radeva; Joan Serrat; Enric Marti edit   pdf
doi  openurl
  Title A snake for model-based segmentation Type Conference Article
  Year 1995 Publication Proc. Conf. Fifth Int Computer Vision Abbreviated Journal  
  Volume Issue Pages 816-821  
  Keywords snakes; elastic matching; model-based segmenta tion  
  Abstract Despite the promising results of numerous applications, the hitherto proposed snake techniques share some common problems: snake attraction by spurious edge points, snake degeneration (shrinking and attening), convergence and stability of the deformation process, snake initialization and local determination of the parameters of elasticity. We argue here that these problems can be solved only when all the snake aspects are considered. The snakes proposed here implement a new potential eld and external force in order to provide a deformation convergence, attraction by both near and far edges as well as snake behaviour selective according to the edge orientation. Furthermore, we conclude that in the case of model-based seg mentation, the internal force should include structural information about the expected snake shape. Experiments using this kind of snakes for segmenting bones in complex hand radiographs show a signi cant improvement.  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes MILAB;ADAS;IAM Approved no  
  Call Number IAM @ iam @ RSM1995 Serial 1634  
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Author Paula Fritzsche; C.Roig; Ana Ripoll; Emilio Luque; Aura Hernandez-Sabate edit   pdf
doi  openurl
  Title A Performance Prediction Methodology for Data-dependent Parallel Applications Type Conference Article
  Year 2006 Publication Proceedings of the IEEE International Conference on Cluster Computing Abbreviated Journal  
  Volume Issue Pages 1-8  
  Keywords  
  Abstract The increase in the use of parallel distributed architectures in order to solve large-scale scientific problems has generated the need for performance prediction for both deterministic applications and non-deterministic applications. In particular, the performance prediction of data dependent programs is an extremely challenging problem because for a specific issue the input datasets may cause different execution times. Generally, a parallel application is characterized as a collection of tasks and their interrelations. If the application is time-critical it is not enough to work with only one value per task, and consequently knowledge of the distribution of task execution times is crucial. The development of a new prediction methodology to estimate the performance of data-dependent parallel applications is the primary target of this study. This approach makes it possible to evaluate the parallel performance of an application without the need of implementation. A real data-dependent arterial structure detection application model is used to apply the methodology proposed. The predicted times obtained using the new methodology for genuine datasets are compared with predicted times that arise from using only one execution value per task. Finally, the experimental study shows that the new methodology generates more precise predictions.  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes IAM Approved no  
  Call Number IAM @ iam @ FRR2006 Serial 1497  
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Author Jaume Garcia; Debora Gil; A.Bajo; M.J.Ledesma-Carbayo; C.SantaMarta edit   pdf
doi  openurl
  Title Influence of the temporal resolution on the quantification of displacement fields in cardiac magnetic resonance tagged images Type Conference Article
  Year 2008 Publication Proc. Computers in Cardiology Abbreviated Journal  
  Volume 35 Issue Pages 785-788  
  Keywords  
  Abstract It is difficult to acquire tagged cardiac MR images with a high temporal and spatial resolution using clinical MR scanners. However, if such images are used for quantifying scores based on motion, it is essential a resolution as high as possible. This paper explores the influence of the temporal resolution of a tagged series on the quantification of myocardial dynamic parameters. To such purpose we have designed a SPAMM (Spatial Modulation of Magnetization) sequence allowing acquisition of sequences at simple and double temporal resolution. Sequences are processed to compute myocardial motion by an automatic technique based on the tracking of the harmonic phase of tagged images (the Harmonic Phase Flow, HPF). The results have been compared to manual tracking of myocardial tags. The error in displacement fields for double resolution sequences reduces 17%.  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor Alan Murray  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes IAM Approved no  
  Call Number IAM @ iam @ GGB2008 Serial 1508  
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Author Jaume Garcia; Joel Barajas; Francesc Carreras; Sandra Pujades; Petia Radeva edit   pdf
doi  isbn
openurl 
  Title An intuitive validation technique to compare local versus global tagged MRI analysis Type Conference Article
  Year 2005 Publication Computers In Cardiology Abbreviated Journal  
  Volume 32 Issue Pages 29–32  
  Keywords  
  Abstract Myocardium appears as a uniform tissue that seen in convectional Magnetic Resonance Images (MRI) shows just the contractile part of its movement. MR Tagging is a unique imaging technique that prints a grid over the tissue which moves according to the underlying movement of the myocardium revealing the true deformation of the cardiac muscle. Optical flow techniques based on spectral information estimate tissue displacement by analyzing information encoded in the phase maps which can be obtained using, local (Gabor) and global (HARP) methods. In this paper we compare both in synthetic and real Tagged MR sequences. We conclude that local method is slightly more accurate than the global one. On the other hand, global method is more efficient as it is much faster and less parameters have to be taken into account  
  Address Lyon (France)  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN 0-7803-9337-6 Medium  
  Area Expedition Conference  
  Notes IAM;MILAB Approved no  
  Call Number IAM @ iam @ GBC2005 Serial 639  
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Author Aura Hernandez-Sabate; Debora Gil; Petia Radeva; E.N.Nofrerias edit   pdf
doi  openurl
  Title Anisotropic processing of image structures for adventitia detection in intravascular ultrasound images Type Conference Article
  Year 2004 Publication Proc. Computers in Cardiology Abbreviated Journal  
  Volume 31 Issue Pages 229-232  
  Keywords  
  Abstract 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  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Chicago (USA) Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes IAM; MILAB Approved no  
  Call Number IAM @ iam @ HGR2004 Serial 1555  
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Author Jaume Garcia; David Rotger; Francesc Carreras; R.Leta; Petia Radeva edit   pdf
doi  isbn
openurl 
  Title Contrast echography segmentation and tracking by trained deformable models Type Conference Article
  Year 2003 Publication Proc. Computers in Cardiology Abbreviated Journal  
  Volume 30 Issue Pages 173-176  
  Keywords  
  Abstract The objective of this work is to segment the human left ventricle myocardium (LVM) in contrast echocardiography imaging and thus track it along a cardiac cycle in order to extract quantitative data about heart function. Ultrasound images are hard to work with due to their speckle appearance. To overcome this we report the combination of active contour models (ACM) or snakes and active shape models (ASM). The ability of ACM in giving closed and smooth curves in addition to the power of the ASM in producing shapes similar to the ones learned, evoke to a robust algorithm. Meanwhile the snake is attracted towards image main features, ASM acts as a correction factor. The algorithm was tested independently on 180 frames and satisfying results were obtained: in 95% the maximum difference between automatic and experts segmentation was less than 12 pixels.  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Centre de Visió per Computador – Dept. Informàtica, UAB Edifici O – Campus UAB, 08193 Bellater Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0276-6547 ISBN 0-7803-8170-X Medium  
  Area Expedition Conference  
  Notes IAM;MILAB Approved no  
  Call Number IAM @ iam @ GRC2003 Serial 1512  
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