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Author Ernest Valveny; Enric Marti edit   pdf
url  doi
openurl 
  Title Application of deformable template matching to symbol recognition in hand-written architectural draw Type Conference Article
  Year 1999 Publication Proceedings of the Fifth International Conference on Abbreviated Journal  
  Volume Issue Pages  
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  Abstract 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.  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Bangalore (India) Editor (down)  
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  Notes DAG;IAM; Approved no  
  Call Number IAM @ iam @ VAM1999a Serial 1657  
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Author Ernest Valveny; Enric Marti edit  openurl
  Title Recognition of lineal symbols in hand-written drawings using deformable template matching Type Conference Article
  Year 1999 Publication Proceedings of the VIII Symposium Nacional de Reconocimiento de Formas y Análisis de Imágenes Abbreviated Journal  
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  Notes DAG;IAM; Approved no  
  Call Number IAM @ iam @ VAM1999 Serial 1658  
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Author Ernest Valveny; Enric Marti edit  openurl
  Title Dimensions analysis in hand-drawn architectural drawings Type Conference Article
  Year 1997 Publication VII National Simposium of Pattern Recognition and image Analysis, SNRFAI´97 Abbreviated Journal  
  Volume Issue Pages 90-91  
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  Publisher Place of Publication CVC-UAB Editor (down)  
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  Area Expedition Conference  
  Notes DAG;IAM; Approved no  
  Call Number IAM @ iam @ VAM1997 Serial 1659  
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Author Ernest Valveny; Ricardo Toledo; Ramon Baldrich; Enric Marti edit  openurl
  Title Combining recognition-based in segmentation-based approaches for graphic symol recognition using deformable template matching Type Conference Article
  Year 2002 Publication Proceeding of the Second IASTED International Conference Visualization, Imaging and Image Proceesing VIIP 2002 Abbreviated Journal  
  Volume Issue Pages 502–507  
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  Notes DAG;RV;CAT;IAM;CIC;ADAS Approved no  
  Call Number IAM @ iam @ VTB2002 Serial 1660  
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Author Lluis Pere de las Heras; Ahmed Sheraz; Marcus Liwicki; Ernest Valveny; Gemma Sanchez edit   pdf
doi  openurl
  Title Statistical Segmentation and Structural Recognition for Floor Plan Interpretation Type Journal Article
  Year 2014 Publication International Journal on Document Analysis and Recognition Abbreviated Journal IJDAR  
  Volume 17 Issue 3 Pages 221-237  
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  Abstract A generic method for floor plan analysis and interpretation is presented in this article. The method, which is mainly inspired by the way engineers draw and interpret floor plans, applies two recognition steps in a bottom-up manner. First, basic building blocks, i.e., walls, doors, and windows are detected using a statistical patch-based segmentation approach. Second, a graph is generated, and structural pattern recognition techniques are applied to further locate the main entities, i.e., rooms of the building. The proposed approach is able to analyze any type of floor plan regardless of the notation used. We have evaluated our method on different publicly available datasets of real architectural floor plans with different notations. The overall detection and recognition accuracy is about 95 %, which is significantly better than any other state-of-the-art method. Our approach is generic enough such that it could be easily adopted to the recognition and interpretation of any other printed machine-generated structured documents.  
  Address  
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  Publisher Springer Berlin Heidelberg Place of Publication Editor (down)  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1433-2833 ISBN Medium  
  Area Expedition Conference  
  Notes DAG; ADAS; 600.076; 600.077 Approved no  
  Call Number HSL2014 Serial 2370  
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Author Palaiahnakote Shivakumara; Anjan Dutta; Trung Quy Phan; Chew Lim Tan; Umapada Pal edit  doi
openurl 
  Title A Novel Mutual Nearest Neighbor based Symmetry for Text Frame Classification in Video Type Journal Article
  Year 2011 Publication Pattern Recognition Abbreviated Journal PR  
  Volume 44 Issue 8 Pages 1671-1683  
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  Abstract In the field of multimedia retrieval in video, text frame classification is essential for text detection, event detection, event boundary detection, etc. We propose a new text frame classification method that introduces a combination of wavelet and median moment with k-means clustering to select probable text blocks among 16 equally sized blocks of a video frame. The same feature combination is used with a new Max–Min clustering at the pixel level to choose probable dominant text pixels in the selected probable text blocks. For the probable text pixels, a so-called mutual nearest neighbor based symmetry is explored with a four-quadrant formation centered at the centroid of the probable dominant text pixels to know whether a block is a true text block or not. If a frame produces at least one true text block then it is considered as a text frame otherwise it is a non-text frame. Experimental results on different text and non-text datasets including two public datasets and our own created data show that the proposed method gives promising results in terms of recall and precision at the block and frame levels. Further, we also show how existing text detection methods tend to misclassify non-text frames as text frames in term of recall and precision at both the block and frame levels.  
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  Notes DAG Approved no  
  Call Number Admin @ si @ SDP2011 Serial 1727  
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Author Lluis Pere de las Heras; Gemma Sanchez edit  doi
isbn  openurl
  Title And-Or Graph Grammar for Architectural Floorplan Representation, Learning and Recognition. A Semantic, Structural and Hierarchical Model Type Conference Article
  Year 2011 Publication 5th Iberian Conference on Pattern Recognition and Image Analysis Abbreviated Journal  
  Volume 6669 Issue Pages 17-24  
  Keywords  
  Abstract This paper presents a syntactic model for architectural floor plan interpretation. A stochastic image grammar over an And-Or graph is inferred to represent the hierarchical, structural and semantic relations between elements of all possible floor plans. This grammar is augmented with three different probabilistic models, learnt from a training set, to account the frequency of that relations. Then, a Bottom-Up/Top-Down parser with a pruning strategy has been used for floor plan recognition. For a given input, the parser generates the most probable parse graph for that document. This graph not only contains the structural and semantic relations of its elements, but also its hierarchical composition, that allows to interpret the floor plan at different levels of abstraction.  
  Address Las Palmas de Gran Canaria. Spain  
  Corporate Author Thesis  
  Publisher Place of Publication Editor (down)  
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  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN 978-3-642-21256-7 Medium  
  Area Expedition Conference IbPRIA  
  Notes DAG Approved no  
  Call Number Admin @ si @ HeS2011 Serial 1736  
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Author Jon Almazan; Alicia Fornes; Ernest Valveny edit  url
doi  isbn
openurl 
  Title A Non-Rigid Feature Extraction Method for Shape Recognition Type Conference Article
  Year 2011 Publication 11th International Conference on Document Analysis and Recognition Abbreviated Journal  
  Volume Issue Pages 987-991  
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  Abstract This paper presents a methodology for shape recognition that focuses on dealing with the difficult problem of large deformations. The proposed methodology consists in a novel feature extraction technique, which uses a non-rigid representation adaptable to the shape. This technique employs a deformable grid based on the computation of geometrical centroids that follows a region partitioning algorithm. Then, a feature vector is extracted by computing pixel density measures around these geometrical centroids. The result is a shape descriptor that adapts its representation to the given shape and encodes the pixel density distribution. The validity of the method when dealing with large deformations has been experimentally shown over datasets composed of handwritten shapes. It has been applied to signature verification and shape recognition tasks demonstrating high accuracy and low computational cost.  
  Address Beijing; China; September 2011  
  Corporate Author Thesis  
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  ISSN ISBN 978-0-7695-4520-2 Medium  
  Area Expedition Conference ICDAR  
  Notes DAG Approved no  
  Call Number Admin @ si @ AFV2011 Serial 1763  
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Author Marçal Rusiñol; R.Roset; Josep Llados; C.Montaner edit  openurl
  Title Automatic Index Generation of Digitized Map Series by Coordinate Extraction and Interpretation Type Journal
  Year 2011 Publication e-Perimetron Abbreviated Journal ePER  
  Volume 6 Issue 4 Pages 219-229  
  Keywords  
  Abstract By means of computer vision algorithms scanned images of maps are processed in order to extract relevant geographic information from printed coordinate pairs. The meaningful information is then transformed into georeferencing information for each single map sheet, and the complete set is compiled to produce a graphical index sheet for the map series along with relevant metadata. The whole process is fully automated and trained to attain maximum effectivity and throughput.  
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  Publisher Place of Publication Editor (down)  
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  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes DAG Approved no  
  Call Number Admin @ si @ RRL2011a Serial 1765  
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Author Sergio Escalera; Alicia Fornes; Oriol Pujol; Josep Llados; Petia Radeva edit  doi
openurl 
  Title Circular Blurred Shape Model for Multiclass Symbol Recognition Type Journal Article
  Year 2011 Publication IEEE Transactions on Systems, Man and Cybernetics (Part B) (IEEE) Abbreviated Journal TSMCB  
  Volume 41 Issue 2 Pages 497-506  
  Keywords  
  Abstract In this paper, we propose a circular blurred shape model descriptor to deal with the problem of symbol detection and classification as a particular case of object recognition. The feature extraction is performed by capturing the spatial arrangement of significant object characteristics in a correlogram structure. The shape information from objects is shared among correlogram regions, where a prior blurring degree defines the level of distortion allowed in the symbol, making the descriptor tolerant to irregular deformations. Moreover, the descriptor is rotation invariant by definition. We validate the effectiveness of the proposed descriptor in both the multiclass symbol recognition and symbol detection domains. In order to perform the symbol detection, the descriptors are learned using a cascade of classifiers. In the case of multiclass categorization, the new feature space is learned using a set of binary classifiers which are embedded in an error-correcting output code design. The results over four symbol data sets show the significant improvements of the proposed descriptor compared to the state-of-the-art descriptors. In particular, the results are even more significant in those cases where the symbols suffer from elastic deformations.  
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  Series Volume Series Issue Edition  
  ISSN 1083-4419 ISBN Medium  
  Area Expedition Conference  
  Notes MILAB; DAG;HuPBA Approved no  
  Call Number Admin @ si @ EFP2011 Serial 1784  
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