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Author Josep Llados; Gemma Sanchez edit  openurl
  Title Graph Matching vs. Graph Parsing in Graphics Recognition: A Combined Approach Type Journal
  Year 2004 Publication International Journal of Pattern Recognition and Artificial Intelligence Abbreviated Journal IJPRAI  
  Volume 18 Issue (up) 3 Pages 455–473  
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  Notes DAG; IF: 0.588 Approved no  
  Call Number DAG @ dag @ LlS2004 Serial 445  
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Author Antonio Lopez; Ernest Valveny; Juan J. Villanueva edit  url
openurl 
  Title Real-time quality control of surgical material packaging by artificial vision Type Journal Article
  Year 2005 Publication Assembly Automation Abbreviated Journal  
  Volume 25 Issue (up) 3 Pages  
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  Abstract IF: 0.061)  
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  Notes ADAS;DAG Approved no  
  Call Number ADAS @ adas @ LVV2005 Serial 552  
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Author Marçal Rusiñol; Josep Llados; Gemma Sanchez edit  doi
openurl 
  Title Symbol Spotting in Vectorized Technical Drawings Through a Lookup Table of Region Strings Type Journal Article
  Year 2010 Publication Pattern Analysis and Applications Abbreviated Journal PAA  
  Volume 13 Issue (up) 3 Pages 321-331  
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  Abstract In this paper, we address the problem of symbol spotting in technical document images applied to scanned and vectorized line drawings. Like any information spotting architecture, our approach has two components. First, symbols are decomposed in primitives which are compactly represented and second a primitive indexing structure aims to efficiently retrieve similar primitives. Primitives are encoded in terms of attributed strings representing closed regions. Similar strings are clustered in a lookup table so that the set median strings act as indexing keys. A voting scheme formulates hypothesis in certain locations of the line drawing image where there is a high presence of regions similar to the queried ones, and therefore, a high probability to find the queried graphical symbol. The proposed approach is illustrated in a framework consisting in spotting furniture symbols in architectural drawings. It has been proved to work even in the presence of noise and distortion introduced by the scanning and raster-to-vector processes.  
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  Publisher Springer-Verlag Place of Publication Editor  
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  Series Volume Series Issue Edition  
  ISSN 1433-7541 ISBN Medium  
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  Notes DAG Approved no  
  Call Number DAG @ dag @ RLS2010 Serial 1165  
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Author Marçal Rusiñol; Agnes Borras; Josep Llados edit  doi
openurl 
  Title Relational Indexing of Vectorial Primitives for Symbol Spotting in Line-Drawing Images Type Journal Article
  Year 2010 Publication Pattern Recognition Letters Abbreviated Journal PRL  
  Volume 31 Issue (up) 3 Pages 188–201  
  Keywords Document image analysis and recognition, Graphics recognition, Symbol spotting ,Vectorial representations, Line-drawings  
  Abstract This paper presents a symbol spotting approach for indexing by content a database of line-drawing images. As line-drawings are digital-born documents designed by vectorial softwares, instead of using a pixel-based approach, we present a spotting method based on vector primitives. Graphical symbols are represented by a set of vectorial primitives which are described by an off-the-shelf shape descriptor. A relational indexing strategy aims to retrieve symbol locations into the target documents by using a combined numerical-relational description of 2D structures. The zones which are likely to contain the queried symbol are validated by a Hough-like voting scheme. In addition, a performance evaluation framework for symbol spotting in graphical documents is proposed. The presented methodology has been evaluated with a benchmarking set of architectural documents achieving good performance results.  
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  Publisher Elsevier Place of Publication Editor  
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  Notes DAG Approved no  
  Call Number DAG @ dag @ RBL2010 Serial 1177  
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Author Alicia Fornes; Josep Llados; Gemma Sanchez; Dimosthenis Karatzas edit  doi
openurl 
  Title Rotation Invariant Hand-Drawn Symbol Recognition based on a Dynamic Time Warping Model Type Journal Article
  Year 2010 Publication International Journal on Document Analysis and Recognition Abbreviated Journal IJDAR  
  Volume 13 Issue (up) 3 Pages 229–241  
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  Abstract One of the major difficulties of handwriting symbol recognition is the high variability among symbols because of the different writer styles. In this paper, we introduce a robust approach for describing and recognizing hand-drawn symbols tolerant to these writer style differences. This method, which is invariant to scale and rotation, is based on the dynamic time warping (DTW) algorithm. The symbols are described by vector sequences, a variation of the DTW distance is used for computing the matching distance, and K-Nearest Neighbor is used to classify them. Our approach has been evaluated in two benchmarking scenarios consisting of hand-drawn symbols. Compared with state-of-the-art methods for symbol recognition, our method shows higher tolerance to the irregular deformations induced by hand-drawn strokes.  
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  Publisher Springer-Verlag Place of Publication Editor  
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  ISSN 1433-2833 ISBN Medium  
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  Notes DAG; IF 2009: 1,213 Approved no  
  Call Number DAG @ dag @ FLS2010a Serial 1288  
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