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Author |
Josep Llados; Horst Bunke; Enric Marti |
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Title |
Structural Recognition of hand drawn floor plans |
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1996 |
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VI National Symposium on Pattern Recognition and Image Analysis |
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Rotational Symmetry; Reflectional Symmetry; String Matching. |
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A system to recognize hand drawn architectural drawings in a CAD environment has been deve- loped. In this paper we focus on its high level interpretation module. To interpret a floor plan, the system must identify several building elements, whose description is stored in a library of pat- terns, as well as their spatial relationships. We propose a structural approach based on subgraph isomorphism techniques to obtain a high-level interpretation of the document. The vectorized input document and the patterns to be recognized are represented by attributed graphs. Discrete relaxation techniques (AC4 algorithm) have been applied to develop the matching algorithm. The process has been divided in three steps: node labeling, local consistency and global consistency verification. The hand drawn creation causes disturbed line drawings with several accuracy errors, which must be taken into account. Here we have identified them and the AC4 algorithm has been adapted to manage them. |
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Cordoba |
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DAG;IAM; |
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IAM @ iam @ LIM1995 |
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1565 |
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Josep Llados; Enric Marti |
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Title |
Graph-edit algorithms for hand-drawn graphical document recognition and their automatic introduction |
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1999 |
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Machine Graphics & Vision journal, special issue on Graph transformation |
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DAG;IAM |
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IAM @ iam @ LIM1999c |
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1569 |
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Josep Llados; Enric Marti |
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Playing with error-tolerant subgraph isomorphism in line drawings |
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1997 |
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VII National Symposium on Pattern Recognition and image Analysis |
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DAG;IAM; |
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IAM @ iam @ LlM1997 |
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1570 |
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Josep Llados; Ernest Valveny; Gemma Sanchez; Enric Marti |
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A Case Study of Pattern Recognition: Symbol Recognition in Graphic Documentsa |
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2003 |
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Proceedings of Pattern Recognition in Information Systems |
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1-13 |
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Angers, France |
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ICEIS Press |
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972-98816-3-4 |
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PRIS'03 |
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DAG;IAM; |
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IAM @ iam @ LVS2003 |
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1576 |
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Josep Llados; Enric Marti |
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Title |
Interpretacio de dibuixos lineals mitjançant tècniques d isomorfisme entre grafs |
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1995 |
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Trobada de Joves Investigadors |
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L’anàlisi de documents té com a objectiu la interpretació automàtica de documents impresos sobre paper, amb la finalitat d’obtenir una descripció simbòlica d’aquests, que permeti el seu emmagatzemament i posterior tractament computacional. Les tècniques basades en grafs relacionals d’atributs permeten representar de manera compacta la informació continguda en dibuixos lineals i mitjançant mecanismes d’isomorfisme entre grafs, reconèixer-hi certes estructures i d’aquesta manera, interpretar el document. En aquest treball es dóna una visió general de les tènciques de grafs aplicades al reconeixement visual d’objectes en problemes d’anàlisi de documents. Aquestes tècniques s’il·lustren amb un exemple de reconeixement de plànols dibuixats a mà alçada. Finalment es proposa la utilització de tècniques de Hough com a mecanisme per accelerar el procés de reconeixement aplicant un cert coneixement sobre el domini en el que es treballa |
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DAG;IAM |
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IAM @ iam @ LlM1995 |
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1578 |
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Author |
Josep Llados; Enric Marti; Jaime Lopez-Krahe |
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A Hough-based method for hatched pattern detection in maps and diagrams |
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1999 |
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Proceeding of the Fifth Int. Conf. Document Analysis and Recognition ICDAR ’99 |
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479-482 |
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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. |
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DAG;IAM; |
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IAM @ iam @ LIM1999b |
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1580 |
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Gemma Sanchez; Josep Llados; Enric Marti |
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Title |
Segmentation and analysis of linial texture in plans |
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1997 |
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Actes de la conférence Artificielle et Complexité. |
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Structural Texture, Voronoi, Hierarchical Clustering, String Matching. |
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The problem of texture segmentation and interpretation is one of the main concerns in the field of document analysis. Graphical documents often contain areas characterized by a structural texture whose recognition allows both the document understanding, and its storage in a more compact way. In this work, we focus on structural linial textures of regular repetition contained in plan documents. Starting from an atributed graph which represents the vectorized input image, we develop a method to segment textured areas and recognize their placement rules. We wish to emphasize that the searched textures do not follow a predefined pattern. Minimal closed loops of the input graph are computed, and then hierarchically clustered. In this hierarchical clustering, a distance function between two closed loops is defined in terms of their areas difference and boundary resemblance computed by a string matching procedure. Finally it is noted that, when the texture consists of isolated primitive elements, the same method can be used after computing a Voronoi Tesselation of the input graph. |
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Paris, France |
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Paris |
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AERFAI |
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DAG;IAM; |
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IAM @ iam @ SLM1997 |
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1649 |
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Gemma Sanchez; Ernest Valveny; Josep Llados; Enric Marti; Oriol Ramos Terrades; N.Lozano; Joan Mas |
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A system for virtual prototyping of architectural projects |
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2003 |
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Proceedings of Fifth IAPR International Workshop on Pattern Recognition |
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65-74 |
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DAG;IAM |
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IAM @ iam @ SVL2003 |
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1650 |
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Ernest Valveny; Enric Marti |
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Learning of structural descriptions of graphic symbols using deformable template matching |
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2001 |
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Proc. Sixth Int Document Analysis and Recognition Conf |
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455-459 |
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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. |
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DAG;IAM; |
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IAM @ iam @ VMA2001 |
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1654 |
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Ernest Valveny; Enric Marti |
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Application of deformable template matching to symbol recognition in hand-written architectural draw |
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1999 |
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Proceedings of the Fifth International Conference on |
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We propose to use deformable template matching as a new approach to recognize characters and lineal symbols in hand-written line drawings, instead of traditional methods based on vectorization and feature extraction. Bayesian formulation of the deformable template matching allows combining fidelity to the ideal shape of the symbol with maximum flexibility to get the best fit to the input image. Lineal nature of symbols can be exploited to define a suitable representation of models and the set of deformations to be applied to them. Matching, however, is done over the original binary image to avoid losing relevant features during vectorization. We have applied this method to hand-written architectural drawings and experimental results demonstrate that symbols with high distortions from ideal shape can be accurately identified. |
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Bangalore (India) |
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DAG;IAM; |
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IAM @ iam @ VAM1999a |
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1657 |
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