Relational indexing of vectorial primitives for symbol spotting in line-drawing images

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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. © 2009 Elsevier B.V. All rights reserved.
Original languageEnglish
Pages (from-to)188-201
JournalPattern Recognition Letters
Issue number3
Publication statusPublished - 1 Feb 2010


  • Document image analysis and recognition
  • Graphics recognition
  • Line-drawings
  • Symbol spotting
  • Vectorial representations


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