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    Shape Description for Automatically Structuring Graphical Data


    Keyes, Laura and Winstanley, Adam C. (2003) Shape Description for Automatically Structuring Graphical Data. In: Graphics Recognition. Recent Advances and Perspectives. Lecture Notes in Computer Science (LNCS) (3088). Springer, pp. 256-264. ISBN 9783540224785

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    Abstract

    This work explores automatic object recognition and semantic capture in vector graphics through shape description. The low-level graphical content of graphical documents, such as a map or architectural drawing, are often captured manually and the encoding of the semantic content seen as an extension of this. The large quantity of new and archived graphical data available on paper makes automatic structuring of such graphical data desirable. Contour shape description techniques, such as Fourier descriptors, moment invariants play an important role in systems for object recognition and representation. However, most work carried out in this area has concentrated on categories of object boundaries representing very specific shapes (for example, a particular type of aircraft). Two classifiers were implemented and proved accurate in their automatic recognition of objects from drawings in different domains. Classical classifier combination techniques were used to improve performance. Further work will employ more complex fusion techniques and it is envisaged they will be used in combination with recognition based on object context using various modelling methods. A demonstration system has been constructed using all these techniques.

    Item Type: Book Section
    Additional Information: Cite this paper as: Keyes L., Winstanley A. (2004) Shape Description for Automatically Structuring Graphical Data. In: Lladós J., Kwon YB. (eds) Graphics Recognition. Recent Advances and Perspectives. GREC 2003. Lecture Notes in Computer Science, vol 3088. Springer, Berlin, Heidelberg
    Keywords: Shape Description; Automatically Structuring Graphical Data; automatic object recognition; semantic capture; vector graphics;
    Academic Unit: Faculty of Science and Engineering > Computer Science
    Item ID: 8107
    Identification Number: https://doi.org/10.1007/978-3-540-25977-0_24
    Depositing User: Dr. Adam Winstanley
    Date Deposited: 30 Mar 2017 14:16
    Publisher: Springer
    Refereed: Yes
    URI:

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