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Author |
Enric Marti; Jordi Regincos; Juan Jose Villanueva; Jaime Lopez-Krahe |
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Title |
Line drawing interpretation as polyhedral objects to man-machine interaction in CAD systems |
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1994 |
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Advances in Pattern Recognition and Image Analysis, |
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158-169 |
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World Scientific Pub. |
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981-02-1872-9 |
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IAM;ISE |
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IAM @ iam @ MRL1994 |
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1609 |
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Author |
Ole Vilhelm-Larsen; Petia Radeva; Enric Marti |
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Title |
Guidelines for choosing optimal parameters of elasticity for snakes |
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Book Chapter |
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Year |
1995 |
Publication |
Computer Analysis Of Images And Patterns |
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LNCS |
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970 |
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106-113 |
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This paper proposes a guidance in the process of choosing and using the parameters of elasticity of a snake in order to obtain a precise segmentation. A new two step procedure is defined based on upper and lower bounds on the parameters. Formulas, by which these bounds can be calculated for real images where parts of the contour may be missing, are presented. Experiments on segmentation of bone structures in X-ray images have verified the usefulness of the new procedure. |
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Lecture Notes in Computer Science |
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MILAB;IAM |
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IAM @ iam @ LRM1995b |
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1558 |
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Author |
Josep Llados; Jaime Lopez-Krahe; Enric Marti |
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Title |
A system to understand hand-drawn floor plans using subgraph isomorphism and Hough transform |
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Book Chapter |
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Year |
1997 |
Publication |
Machine Vision and Applications |
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10 |
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3 |
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150-158 |
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Line drawings – Hough transform – Graph matching – CAD systems – Graphics recognition |
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Presently, man-machine interface development is a widespread research activity. A system to understand hand drawn architectural drawings in a CAD environment is presented in this paper. To understand a document, we have to identify its building elements and their structural properties. An attributed graph structure is chosen as a symbolic representation of the input document and the patterns to recognize in it. An inexact subgraph isomorphism procedure using relaxation labeling techniques is performed. In this paper we focus on how to speed up the matching. There is a building element, the walls, characterized by a hatching pattern. Using a straight line Hough transform (SLHT)-based method, we recognize this pattern, characterized by parallel straight lines, and remove from the input graph the edges belonging to this pattern. The isomorphism is then applied to the remainder of the input graph. When all the building elements have been recognized, the document is redrawn, correcting the inaccurate strokes obtained from a hand-drawn input. |
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IAM @ iam @ LLM1997a |
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1566 |
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Author |
Josep Llados; Gemma Sanchez; Enric Marti |
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Title |
A string based method to recognize symbols and structural textures in architectural plans |
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Book Chapter |
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Year |
1998 |
Publication |
Graphics Recognition Algorithms and Systems Second International Workshop, GREC' 97 Nancy, France, August 22–23, 1997 Selected Papers |
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LNCS |
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1389 |
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1998 |
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91-103 |
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This paper deals with the recognition of symbols and structural textures in architectural plans using string matching techniques. A plan is represented by an attributed graph whose nodes represent characteristic points and whose edges represent segments. Symbols and textures can be seen as a set of regions, i.e. closed loops in the graph, with a particular arrangement. The search for a symbol involves a graph matching between the regions of a model graph and the regions of the graph representing the document. Discriminating a texture means a clustering of neighbouring regions of this graph. Both procedures involve a similarity measure between graph regions. A string codification is used to represent the sequence of outlining edges of a region. Thus, the similarity between two regions is defined in terms of the string edit distance between their boundary strings. The use of string matching allows the recognition method to work also under presence of distortion. |
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Springer Link |
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DAG; IAM |
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IAM @ iam @ SLE1998 |
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1573 |
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Author |
Enric Marti; Jordi Vitria; Alberto Sanfeliu |
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Title |
Reconocimiento de Formas y Análisis de Imágenes |
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Year |
1998 |
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Asociación Española de Reconocimientos de Formas y Análisis de Imágenes |
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Los sistemas actuales de reconocimiento automático del lenguaje oral se basan en dos etapas básicas de procesado: la parametrización, que extrae la evolución temporal de los parámetros que caracterizan la voz, y el reconocimiento propiamente dicho, que identifica la cadena de palabras de la elocución recibida con ayuda de los modelos que representan el conocimiento adquirido en la etapa de aprendizaje. Tomando como línea divisoria la palabra, dichos modelos son de tipo acústicofonético o gramatical. Los primeros caracterizan las palabras incluidas en el vocabulario de la aplicación o tarea a la que está orientado el sistema de reconocimiento, usando a menudo para ello modelos de unidades de habla de extensión inferior a la palabra, es decir, de unidades subléxicas. Por otro lado, la gramática incluye el conocimiento acerca de las combinaciones permitidas de palabras para formar las frases o su probabilidad. Queda fuera del esquema la denominada comprensión del habla, que utiliza adicionalmente el conocimiento semántico y pragmático para captar el significado de la elocución de entrada al sistema a partir de la cadena (o cadenas alternativas) de palabras que suministra el reconocedor. |
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AERFAI |
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84–922529–4–4 |
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IAM;OR;MV |
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Call Number |
IAM @ iam @ MVS1998 |
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1620 |
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Author |
Josep Llados; Ernest Valveny; Gemma Sanchez; Enric Marti |
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Title |
Symbol recognition: current advances and perspectives |
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Book Chapter |
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Year |
2002 |
Publication |
Graphics Recognition Algorithms And Applications |
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LNCS |
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2390 |
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104-128 |
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The recognition of symbols in graphic documents is an intensive research activity in the community of pattern recognition and document analysis. A key issue in the interpretation of maps, engineering drawings, diagrams, etc. is the recognition of domain dependent symbols according to a symbol database. In this work we first review the most outstanding symbol recognition methods from two different points of view: application domains and pattern recognition methods. In the second part of the paper, open and unaddressed problems involved in symbol recognition are described, analyzing their current state of art and discussing future research challenges. Thus, issues such as symbol representation, matching, segmentation, learning, scalability of recognition methods and performance evaluation are addressed in this work. Finally, we discuss the perspectives of symbol recognition concerning to new paradigms such as user interfaces in handheld computers or document database and WWW indexing by graphical content. |
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London, UK |
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Springer-Verlag |
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Dorothea Blostein and Young- Bin Kwon |
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Lecture Notes in Computer Science |
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LNCS |
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3-540-44066-6 |
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GREC |
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DAG; IAM; |
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IAM @ iam @ LVS2002 |
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1572 |
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Author |
Debora Gil; Petia Radeva |
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Title |
Curvature Vector Flow to Assure Convergent Deformable Models for Shape Modelling |
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Book Chapter |
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Year |
2003 |
Publication |
Energy Minimization Methods In Computer Vision And Pattern Recognition |
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LNCS |
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2683 |
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357-372 |
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Initial condition; Convex shape; Non convex analysis; Increase; Segmentation; Gradient; Standard; Standards; Concave shape; Flow models; Tracking; Edge detection; Curvature |
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Poor convergence to concave shapes is a main limitation of snakes as a standard segmentation and shape modelling technique. The gradient of the external energy of the snake represents a force that pushes the snake into concave regions, as its internal energy increases when new inexion points are created. In spite of the improvement of the external energy by the gradient vector ow technique, highly non convex shapes can not be obtained, yet. In the present paper, we develop a new external energy based on the geometry of the curve to be modelled. By tracking back the deformation of a curve that evolves by minimum curvature ow, we construct a distance map that encapsulates the natural way of adapting to non convex shapes. The gradient of this map, which we call curvature vector ow (CVF), is capable of attracting a snake towards any contour, whatever its geometry. Our experiments show that, any initial snake condition converges to the curve to be modelled in optimal time. |
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Springer, Berlin |
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Lisbon, PORTUGAL |
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Springer, B. |
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Lecture Notes in Computer Science |
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LNCS |
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0302-9743 |
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3-540-40498-8 |
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IAM;MILAB |
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IAM @ iam @ GIR2003b |
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1535 |
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Author |
Jaume Garcia; Petia Radeva; Francesc Carreras |
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Title |
Combining Spectral and Active Shape methods to Track Tagged MRI |
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2004 |
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Recent Advances in Artificial Intelligence Research and Development |
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37-44 |
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MR; tagged MR; ASM; LV segmentation; motion estimation. |
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Tagged magnetic resonance is a very usefull and unique tool that provides a complete local and global knowledge of the left ventricle (LV) motion. In this article we introduce a method capable of tracking and segmenting the LV. Spectral methods are applied in order to obtain the so called HARP images which encode information about movement and are the base for LV point-tracking. For segmentation we use Active Shapes (ASM) that model LV shape variation in order to overcome possible local misplacements of the boundary. We finally show experiments on both synthetic and real data which appear to be very promising. |
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IOS Press |
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CCIA |
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IAM;MILAB |
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IAM @ iam @ GRC2004 |
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1488 |
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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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84-933652-0-3 |
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IAM; |
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IAM @ iam @ GIL2004 |
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1517 |
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Debora Gil; Petia Radeva |
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Title |
Inhibition of False Landmarks |
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2004 |
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Recent Advances in Artificial Intelligence Research and Development |
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233-244 |
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We argue that a corner detector should be based on the degree of continuity of the tangent vector to the image level sets, work on the image domain and need no assumptions on neither the image local structure nor the particular geometry of the corner/junction. An operator measuring the degree of differentiability of the projection matrix on the image gradient fulfills the above requirements. Its high sensitivity to changes in vector directions makes it suitable for landmark location in real images prone to need smoothing to reduce the impact of noise. Because using smoothing kernels leads to corner misplacement, we suggest an alternative fake response remover based on the receptive field inhibition of spurious details. The combination of both orientation discontinuity detection and noise inhibition produce our Inhibition Orientation Energy (IOE) landmark locator. |
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IOS Press |
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Barcelona (Spain) |
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al, J.V. et |
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IAM @ iam @ GiR2004a |
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1533 |
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